Uses of Class
ai.sklearn4j.core.libraries.numpy.NumpyArray
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Uses of NumpyArray in ai.sklearn4j.base
Fields in ai.sklearn4j.base declared as NumpyArray Modifier and Type Field Description protected NumpyArray<Double>ClassifierMixin. classCountsThe frequency of each class in the training set.protected NumpyArray<Long>ClassifierMixin. classesThe list of class IDs.Methods in ai.sklearn4j.base that return NumpyArray Modifier and Type Method Description NumpyArray<Double>ClassifierMixin. getClassCounts()Gets the class counts.NumpyArray<Long>ClassifierMixin. getClasses()Gets the classes.abstract NumpyArray<Long>ClassifierMixin. predict(NumpyArray<Double> x)Perform classification on an array of test vectors X.abstract NumpyArray<Double>ClassifierMixin. predictLogProbabilities(NumpyArray<Double> x)Return log-probability estimates for the test vector X.abstract NumpyArray<Double>ClassifierMixin. predictProbabilities(NumpyArray<Double> x)Return probability estimates for the test vector X.Methods in ai.sklearn4j.base with parameters of type NumpyArray Modifier and Type Method Description abstract NumpyArray<Long>ClassifierMixin. predict(NumpyArray<Double> x)Perform classification on an array of test vectors X.abstract NumpyArray<Double>ClassifierMixin. predictLogProbabilities(NumpyArray<Double> x)Return log-probability estimates for the test vector X.abstract NumpyArray<Double>ClassifierMixin. predictProbabilities(NumpyArray<Double> x)Return probability estimates for the test vector X.voidClassifierMixin. setClassCounts(NumpyArray<Double> classCounts)Sets the class counts.voidClassifierMixin. setClasses(NumpyArray<Long> classes)Sets the classes. -
Uses of NumpyArray in ai.sklearn4j.core.libraries
Methods in ai.sklearn4j.core.libraries that return NumpyArray Modifier and Type Method Description static NumpyArray<Double>Scipy. logSumExponent(NumpyArray<Double> data, int axis)Compute the log of the sum of exponentials of input elements.Methods in ai.sklearn4j.core.libraries with parameters of type NumpyArray Modifier and Type Method Description static NumpyArray<Double>Scipy. logSumExponent(NumpyArray<Double> data, int axis)Compute the log of the sum of exponentials of input elements. -
Uses of NumpyArray in ai.sklearn4j.core.libraries.numpy
Methods in ai.sklearn4j.core.libraries.numpy that return NumpyArray Modifier and Type Method Description static NumpyArrayNumpy. abs(NumpyArray<Double> array)Calculate the absolute value element-wise.static NumpyArrayNumpy. add(NumpyArray array, byte value)Adds a byte value to numpy arrays.static NumpyArray<Double>Numpy. add(NumpyArray array, double value)Adds a double value to numpy arrays.static NumpyArray<Float>Numpy. add(NumpyArray array, float value)Adds a float value to numpy arrays.static NumpyArrayNumpy. add(NumpyArray array, int value)Adds a int value to numpy arrays.static NumpyArrayNumpy. add(NumpyArray array, long value)Adds a long value to numpy arrays.static NumpyArrayNumpy. add(NumpyArray array, short value)Adds a short value to numpy arrays.static NumpyArrayNumpy. add(NumpyArray a1, NumpyArray a2)Adds two numpy arrays.NumpyArray<OutputType>NumpyArrayOperationWithAxisReduction. apply(NumpyArray<InputType> array, int axis, boolean keepDimensions)Applies the operation on the numpy array.static <Type> NumpyArray<Long>Numpy. argmax(NumpyArray<Type> array, int axis, boolean keepDimensions)Returns the indices of the maximum values along an axis.static NumpyArray<Double>Numpy. arrayMax(NumpyArray<Double> array, int axis, boolean keepDimensions)Returns the maximum values along an axis.static NumpyArray<Double>NumpyArrayFactory. arrayOfDoubleWithShape(int[] shape)Create a numpy array of double with specified shape.static NumpyArray<Float>NumpyArrayFactory. arrayOfFloatWithShape(int[] shape)Create a numpy array of float with specified shape.static NumpyArray<Short>NumpyArrayFactory. arrayOfInt16WithShape(int[] shape)Create a numpy array of short with specified shape.static NumpyArray<Integer>NumpyArrayFactory. arrayOfInt32WithShape(int[] shape)Create a numpy array of int with specified shape.static NumpyArray<Long>NumpyArrayFactory. arrayOfInt64WithShape(int[] shape)Create a numpy array of long with specified shape.static NumpyArray<Byte>NumpyArrayFactory. arrayOfInt8WithShape(int[] shape)Create a numpy array of byte with specified shape.static NumpyArray<Byte>Numpy. atLeast2D(byte value)Wraps an atomic byte value into a 2 dimensional array.static NumpyArray<Double>Numpy. atLeast2D(double value)Wraps an atomic double value into a 2 dimensional array.static NumpyArray<Float>Numpy. atLeast2D(float value)Wraps an atomic float value into a 2 dimensional array.static NumpyArray<Integer>Numpy. atLeast2D(int value)Wraps an atomic int value into a 2 dimensional array.static NumpyArray<Long>Numpy. atLeast2D(long value)Wraps an atomic long value into a 2 dimensional array.static NumpyArray<Short>Numpy. atLeast2D(short value)Wraps an atomic short value into a 2 dimensional array.static <Type> NumpyArray<Type>Numpy. atLeast2D(NumpyArray<Type> array)Wraps a numpy array into a 2 dimensional array if the number dimensions is less than 2.static NumpyArray<Double>Numpy. clip(NumpyArray<Double> array, double min, double max)Clip (limit) the values in an array.static NumpyArrayNumpyArrayFactory. createArrayOfShapeAndTypeInfo(boolean isFloatingPoint, int size, int[] shape)Creates a numpy array with a specified shape that can store values with specified characteristics.static NumpyArrayNumpyArrayFactory. createArrayOfShapeAndTypeInfo(NumpyArray other)Creates a numpy array of the same dimension and data type of the provided one.NumpyArray<OutputType>NumpyArrayOperationWithAxisReduction. createInstanceResultNumpyArray(int[] shape)Instantiate the result numpy array.static NumpyArray<Double>Numpy. divide(NumpyArray<Double> array, double factor)Divides a numpy array by a double value.static NumpyArray<Float>Numpy. divide(NumpyArray<Float> array, float factor)Divides a numpy array by a float value.static NumpyArrayNumpy. divide(NumpyArray a1, NumpyArray a2)Divides two numpy arrays.static NumpyArray<Double>Numpy. exp(NumpyArray array)Calculate the exponential of all elements in the input array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[] array)Create a numpy array wrapper over a 1 dimension byte array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[][] array)Create a numpy array wrapper over a 2 dimension byte array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[][][] array)Create a numpy array wrapper over a 3 dimension byte array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[][][][] array)Create a numpy array wrapper over a 4 dimension byte array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[][][][][] array)Create a numpy array wrapper over a 5 dimension byte array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[][][][][][] array)Create a numpy array wrapper over a 6 dimension byte array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[][][][][][][] array)Create a numpy array wrapper over a 7 dimension byte array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[][][][][][][][] array)Create a numpy array wrapper over a 8 dimension byte array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[][][][][][][][][] array)Create a numpy array wrapper over a 9 dimension byte array.static NumpyArray<Byte>NumpyArrayFactory. from(byte[][][][][][][][][][] array)Create a numpy array wrapper over a 10 dimension byte array.static NumpyArray<Double>NumpyArrayFactory. from(double[] array)Create a numpy array wrapper over a 1 dimension double array.static NumpyArray<Double>NumpyArrayFactory. from(double[][] array)Create a numpy array wrapper over a 2 dimension double array.static NumpyArray<Double>NumpyArrayFactory. from(double[][][] array)Create a numpy array wrapper over a 3 dimension double array.static NumpyArray<Double>NumpyArrayFactory. from(double[][][][] array)Create a numpy array wrapper over a 4 dimension double array.static NumpyArray<Double>NumpyArrayFactory. from(double[][][][][] array)Create a numpy array wrapper over a 5 dimension double array.static NumpyArray<Double>NumpyArrayFactory. from(double[][][][][][] array)Create a numpy array wrapper over a 6 dimension double array.static NumpyArray<Double>NumpyArrayFactory. from(double[][][][][][][] array)Create a numpy array wrapper over a 7 dimension double array.static NumpyArray<Double>NumpyArrayFactory. from(double[][][][][][][][] array)Create a numpy array wrapper over a 8 dimension double array.static NumpyArray<Double>NumpyArrayFactory. from(double[][][][][][][][][] array)Create a numpy array wrapper over a 9 dimension double array.static NumpyArray<Double>NumpyArrayFactory. from(double[][][][][][][][][][] array)Create a numpy array wrapper over a 10 dimension double array.static NumpyArray<Float>NumpyArrayFactory. from(float[] array)Create a numpy array wrapper over a 1 dimension float array.static NumpyArray<Float>NumpyArrayFactory. from(float[][] array)Create a numpy array wrapper over a 2 dimension float array.static NumpyArray<Float>NumpyArrayFactory. from(float[][][] array)Create a numpy array wrapper over a 3 dimension float array.static NumpyArray<Float>NumpyArrayFactory. from(float[][][][] array)Create a numpy array wrapper over a 4 dimension float array.static NumpyArray<Float>NumpyArrayFactory. from(float[][][][][] array)Create a numpy array wrapper over a 5 dimension float array.static NumpyArray<Float>NumpyArrayFactory. from(float[][][][][][] array)Create a numpy array wrapper over a 6 dimension float array.static NumpyArray<Float>NumpyArrayFactory. from(float[][][][][][][] array)Create a numpy array wrapper over a 7 dimension float array.static NumpyArray<Float>NumpyArrayFactory. from(float[][][][][][][][] array)Create a numpy array wrapper over a 8 dimension float array.static NumpyArray<Float>NumpyArrayFactory. from(float[][][][][][][][][] array)Create a numpy array wrapper over a 9 dimension float array.static NumpyArray<Float>NumpyArrayFactory. from(float[][][][][][][][][][] array)Create a numpy array wrapper over a 10 dimension float array.static NumpyArray<Integer>NumpyArrayFactory. from(int[] array)Create a numpy array wrapper over a 1 dimension int array.static NumpyArray<Integer>NumpyArrayFactory. from(int[][] array)Create a numpy array wrapper over a 2 dimension int array.static NumpyArray<Integer>NumpyArrayFactory. from(int[][][] array)Create a numpy array wrapper over a 3 dimension int array.static NumpyArray<Integer>NumpyArrayFactory. from(int[][][][] array)Create a numpy array wrapper over a 4 dimension int array.static NumpyArray<Integer>NumpyArrayFactory. from(int[][][][][] array)Create a numpy array wrapper over a 5 dimension int array.static NumpyArray<Integer>NumpyArrayFactory. from(int[][][][][][] array)Create a numpy array wrapper over a 6 dimension int array.static NumpyArray<Integer>NumpyArrayFactory. from(int[][][][][][][] array)Create a numpy array wrapper over a 7 dimension int array.static NumpyArray<Integer>NumpyArrayFactory. from(int[][][][][][][][] array)Create a numpy array wrapper over a 8 dimension int array.static NumpyArray<Integer>NumpyArrayFactory. from(int[][][][][][][][][] array)Create a numpy array wrapper over a 9 dimension int array.static NumpyArray<Integer>NumpyArrayFactory. from(int[][][][][][][][][][] array)Create a numpy array wrapper over a 10 dimension int array.static NumpyArray<Long>NumpyArrayFactory. from(long[] array)Create a numpy array wrapper over a 1 dimension long array.static NumpyArray<Long>NumpyArrayFactory. from(long[][] array)Create a numpy array wrapper over a 2 dimension long array.static NumpyArray<Long>NumpyArrayFactory. from(long[][][] array)Create a numpy array wrapper over a 3 dimension long array.static NumpyArray<Long>NumpyArrayFactory. from(long[][][][] array)Create a numpy array wrapper over a 4 dimension long array.static NumpyArray<Long>NumpyArrayFactory. from(long[][][][][] array)Create a numpy array wrapper over a 5 dimension long array.static NumpyArray<Long>NumpyArrayFactory. from(long[][][][][][] array)Create a numpy array wrapper over a 6 dimension long array.static NumpyArray<Long>NumpyArrayFactory. from(long[][][][][][][] array)Create a numpy array wrapper over a 7 dimension long array.static NumpyArray<Long>NumpyArrayFactory. from(long[][][][][][][][] array)Create a numpy array wrapper over a 8 dimension long array.static NumpyArray<Long>NumpyArrayFactory. from(long[][][][][][][][][] array)Create a numpy array wrapper over a 9 dimension long array.static NumpyArray<Long>NumpyArrayFactory. from(long[][][][][][][][][][] array)Create a numpy array wrapper over a 10 dimension long array.static NumpyArray<Short>NumpyArrayFactory. from(short[] array)Create a numpy array wrapper over a 1 dimension short array.static NumpyArray<Short>NumpyArrayFactory. from(short[][] array)Create a numpy array wrapper over a 2 dimension short array.static NumpyArray<Short>NumpyArrayFactory. from(short[][][] array)Create a numpy array wrapper over a 3 dimension short array.static NumpyArray<Short>NumpyArrayFactory. from(short[][][][] array)Create a numpy array wrapper over a 4 dimension short array.static NumpyArray<Short>NumpyArrayFactory. from(short[][][][][] array)Create a numpy array wrapper over a 5 dimension short array.static NumpyArray<Short>NumpyArrayFactory. from(short[][][][][][] array)Create a numpy array wrapper over a 6 dimension short array.static NumpyArray<Short>NumpyArrayFactory. from(short[][][][][][][] array)Create a numpy array wrapper over a 7 dimension short array.static NumpyArray<Short>NumpyArrayFactory. from(short[][][][][][][][] array)Create a numpy array wrapper over a 8 dimension short array.static NumpyArray<Short>NumpyArrayFactory. from(short[][][][][][][][][] array)Create a numpy array wrapper over a 9 dimension short array.static NumpyArray<Short>NumpyArrayFactory. from(short[][][][][][][][][][] array)Create a numpy array wrapper over a 10 dimension short array.static NumpyArray<Double>Numpy. log(NumpyArray array)Natural logarithm, element-wise.static NumpyArray<Double>Numpy. multiply(NumpyArray<Double> array, double factor)Multiplies a numpy array by a double value.static NumpyArray<Float>Numpy. multiply(NumpyArray<Float> array, float factor)Multiplies a numpy array by a float value.static NumpyArrayNumpy. multiply(NumpyArray a1, NumpyArray a2)Multiplies two numpy arrays.static NumpyArray<Double>Numpy. pow(NumpyArray array, double power)Performs an element-wise power operation on a given NumpyArray.static NumpyArray<Double>Numpy. sqrt(NumpyArray array)Return the non-negative square-root of an array, element-wise.static NumpyArrayNumpy. squeeze(NumpyArray array)Remove axes of length one from the array.static NumpyArrayNumpy. subtract(NumpyArray array, byte value)Subtract a byte value from numpy arrays.static NumpyArray<Double>Numpy. subtract(NumpyArray array, double value)Subtract a double value from numpy arrays.static NumpyArray<Float>Numpy. subtract(NumpyArray array, float value)Subtract a float value from numpy arrays.static NumpyArrayNumpy. subtract(NumpyArray array, int value)Subtract a int value from numpy arrays.static NumpyArrayNumpy. subtract(NumpyArray array, long value)Subtract a long value from numpy arrays.static NumpyArrayNumpy. subtract(NumpyArray array, short value)Subtract a short value from numpy arrays.static NumpyArrayNumpy. subtract(NumpyArray a1, NumpyArray a2)Subtract two numpy arrays.static NumpyArrayNumpy. sum(NumpyArray array, int axis, boolean keepDimensions)Sums the values of a NumpyArray along a specified axis.NumpyArrayINumpyArrayWrapper. transpose()Transposes a numpy array by reversing its dimensions.NumpyArray<Type>NumpyArray. transpose()Transposes an array by reversing the order of its dimensions.NumpyArrayINumpyArrayWrapper. wrapInnerSubsetArray(int... indices)Wraps a subset of the numpy array.NumpyArray<Type>NumpyArray. wrapInnerSubsetArray(int... indices)Wraps a subset of the numpy array.Methods in ai.sklearn4j.core.libraries.numpy with parameters of type NumpyArray Modifier and Type Method Description static NumpyArrayNumpy. abs(NumpyArray<Double> array)Calculate the absolute value element-wise.static NumpyArrayNumpy. add(NumpyArray array, byte value)Adds a byte value to numpy arrays.static NumpyArray<Double>Numpy. add(NumpyArray array, double value)Adds a double value to numpy arrays.static NumpyArray<Float>Numpy. add(NumpyArray array, float value)Adds a float value to numpy arrays.static NumpyArrayNumpy. add(NumpyArray array, int value)Adds a int value to numpy arrays.static NumpyArrayNumpy. add(NumpyArray array, long value)Adds a long value to numpy arrays.static NumpyArrayNumpy. add(NumpyArray array, short value)Adds a short value to numpy arrays.static NumpyArrayNumpy. add(NumpyArray a1, NumpyArray a2)Adds two numpy arrays.NumpyArray<OutputType>NumpyArrayOperationWithAxisReduction. apply(NumpyArray<InputType> array, int axis, boolean keepDimensions)Applies the operation on the numpy array.voidNumpyArray. applyToEachElementAnsSaveToTarget(NumpyArray target, INumpyArrayElementOperation<Type> operation)Applies a provided operation on every element of the array and stores it in a specified target array.static <Type> NumpyArray<Long>Numpy. argmax(NumpyArray<Type> array, int axis, boolean keepDimensions)Returns the indices of the maximum values along an axis.static NumpyArray<Double>Numpy. arrayMax(NumpyArray<Double> array, int axis, boolean keepDimensions)Returns the maximum values along an axis.static <Type> NumpyArray<Type>Numpy. atLeast2D(NumpyArray<Type> array)Wraps a numpy array into a 2 dimensional array if the number dimensions is less than 2.static NumpyArray<Double>Numpy. clip(NumpyArray<Double> array, double min, double max)Clip (limit) the values in an array.static NumpyArrayNumpyArrayFactory. createArrayOfShapeAndTypeInfo(NumpyArray other)Creates a numpy array of the same dimension and data type of the provided one.static NumpyArray<Double>Numpy. divide(NumpyArray<Double> array, double factor)Divides a numpy array by a double value.static NumpyArray<Float>Numpy. divide(NumpyArray<Float> array, float factor)Divides a numpy array by a float value.static NumpyArrayNumpy. divide(NumpyArray a1, NumpyArray a2)Divides two numpy arrays.static NumpyArray<Double>Numpy. exp(NumpyArray array)Calculate the exponential of all elements in the input array.static NumpyArray<Double>Numpy. log(NumpyArray array)Natural logarithm, element-wise.static NumpyArray<Double>Numpy. multiply(NumpyArray<Double> array, double factor)Multiplies a numpy array by a double value.static NumpyArray<Float>Numpy. multiply(NumpyArray<Float> array, float factor)Multiplies a numpy array by a float value.static NumpyArrayNumpy. multiply(NumpyArray a1, NumpyArray a2)Multiplies two numpy arrays.static NumpyArray<Double>Numpy. pow(NumpyArray array, double power)Performs an element-wise power operation on a given NumpyArray.static NumpyArray<Double>Numpy. sqrt(NumpyArray array)Return the non-negative square-root of an array, element-wise.static NumpyArrayNumpy. squeeze(NumpyArray array)Remove axes of length one from the array.static NumpyArrayNumpy. subtract(NumpyArray array, byte value)Subtract a byte value from numpy arrays.static NumpyArray<Double>Numpy. subtract(NumpyArray array, double value)Subtract a double value from numpy arrays.static NumpyArray<Float>Numpy. subtract(NumpyArray array, float value)Subtract a float value from numpy arrays.static NumpyArrayNumpy. subtract(NumpyArray array, int value)Subtract a int value from numpy arrays.static NumpyArrayNumpy. subtract(NumpyArray array, long value)Subtract a long value from numpy arrays.static NumpyArrayNumpy. subtract(NumpyArray array, short value)Subtract a short value from numpy arrays.static NumpyArrayNumpy. subtract(NumpyArray a1, NumpyArray a2)Subtract two numpy arrays.static NumpyArrayNumpy. sum(NumpyArray array, int axis, boolean keepDimensions)Sums the values of a NumpyArray along a specified axis. -
Uses of NumpyArray in ai.sklearn4j.core.libraries.numpy.wrappers
Methods in ai.sklearn4j.core.libraries.numpy.wrappers that return NumpyArray Modifier and Type Method Description NumpyArrayDim10DoubleNumpyWrapper. transpose()NumpyArrayDim10FloatNumpyWrapper. transpose()NumpyArrayDim10Int16NumpyWrapper. transpose()NumpyArrayDim10Int32NumpyWrapper. transpose()NumpyArrayDim10Int64NumpyWrapper. transpose()NumpyArrayDim10Int8NumpyWrapper. transpose()NumpyArrayDim1DoubleNumpyWrapper. transpose()NumpyArrayDim1FloatNumpyWrapper. transpose()NumpyArrayDim1Int16NumpyWrapper. transpose()NumpyArrayDim1Int32NumpyWrapper. transpose()NumpyArrayDim1Int64NumpyWrapper. transpose()NumpyArrayDim1Int8NumpyWrapper. transpose()NumpyArrayDim2DoubleNumpyWrapper. transpose()NumpyArrayDim2FloatNumpyWrapper. transpose()NumpyArrayDim2Int16NumpyWrapper. transpose()NumpyArrayDim2Int32NumpyWrapper. transpose()NumpyArrayDim2Int64NumpyWrapper. transpose()NumpyArrayDim2Int8NumpyWrapper. transpose()NumpyArrayDim3DoubleNumpyWrapper. transpose()NumpyArrayDim3FloatNumpyWrapper. transpose()NumpyArrayDim3Int16NumpyWrapper. transpose()NumpyArrayDim3Int32NumpyWrapper. transpose()NumpyArrayDim3Int64NumpyWrapper. transpose()NumpyArrayDim3Int8NumpyWrapper. transpose()NumpyArrayDim4DoubleNumpyWrapper. transpose()NumpyArrayDim4FloatNumpyWrapper. transpose()NumpyArrayDim4Int16NumpyWrapper. transpose()NumpyArrayDim4Int32NumpyWrapper. transpose()NumpyArrayDim4Int64NumpyWrapper. transpose()NumpyArrayDim4Int8NumpyWrapper. transpose()NumpyArrayDim5DoubleNumpyWrapper. transpose()NumpyArrayDim5FloatNumpyWrapper. transpose()NumpyArrayDim5Int16NumpyWrapper. transpose()NumpyArrayDim5Int32NumpyWrapper. transpose()NumpyArrayDim5Int64NumpyWrapper. transpose()NumpyArrayDim5Int8NumpyWrapper. transpose()NumpyArrayDim6DoubleNumpyWrapper. transpose()NumpyArrayDim6FloatNumpyWrapper. transpose()NumpyArrayDim6Int16NumpyWrapper. transpose()NumpyArrayDim6Int32NumpyWrapper. transpose()NumpyArrayDim6Int64NumpyWrapper. transpose()NumpyArrayDim6Int8NumpyWrapper. transpose()NumpyArrayDim7DoubleNumpyWrapper. transpose()NumpyArrayDim7FloatNumpyWrapper. transpose()NumpyArrayDim7Int16NumpyWrapper. transpose()NumpyArrayDim7Int32NumpyWrapper. transpose()NumpyArrayDim7Int64NumpyWrapper. transpose()NumpyArrayDim7Int8NumpyWrapper. transpose()NumpyArrayDim8DoubleNumpyWrapper. transpose()NumpyArrayDim8FloatNumpyWrapper. transpose()NumpyArrayDim8Int16NumpyWrapper. transpose()NumpyArrayDim8Int32NumpyWrapper. transpose()NumpyArrayDim8Int64NumpyWrapper. transpose()NumpyArrayDim8Int8NumpyWrapper. transpose()NumpyArrayDim9DoubleNumpyWrapper. transpose()NumpyArrayDim9FloatNumpyWrapper. transpose()NumpyArrayDim9Int16NumpyWrapper. transpose()NumpyArrayDim9Int32NumpyWrapper. transpose()NumpyArrayDim9Int64NumpyWrapper. transpose()NumpyArrayDim9Int8NumpyWrapper. transpose()NumpyArrayDim10DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim10FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim10Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim10Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim10Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim10Int8NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim1DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim1FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim1Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim1Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim1Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim1Int8NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim2DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim2FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim2Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim2Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim2Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim2Int8NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim3DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim3FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim3Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim3Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim3Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim3Int8NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim4DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim4FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim4Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim4Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim4Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim4Int8NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim5DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim5FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim5Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim5Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim5Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim5Int8NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim6DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim6FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim6Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim6Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim6Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim6Int8NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim7DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim7FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim7Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim7Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim7Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim7Int8NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim8DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim8FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim8Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim8Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim8Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim8Int8NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim9DoubleNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim9FloatNumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim9Int16NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim9Int32NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim9Int64NumpyWrapper. wrapInnerSubsetArray(int... indices)NumpyArrayDim9Int8NumpyWrapper. wrapInnerSubsetArray(int... indices) -
Uses of NumpyArray in ai.sklearn4j.core.packaging
Methods in ai.sklearn4j.core.packaging that return NumpyArray Modifier and Type Method Description NumpyArrayBinaryModelPackage. readNumpyArray()Read a multidimensional numpy array from the stream. -
Uses of NumpyArray in ai.sklearn4j.core.packaging.loaders
Methods in ai.sklearn4j.core.packaging.loaders with parameters of type NumpyArray Modifier and Type Method Description voidIScikitLearnLoaderNumpyArrayFieldSetter. setNumpyArrayField(ObjectType obj, NumpyArray value)Sets a numpy array value into a scikit-learn object.Method parameters in ai.sklearn4j.core.packaging.loaders with type arguments of type NumpyArray Modifier and Type Method Description voidIScikitLearnLoaderListOfNumpyArrayFieldSetter. setListOfNumpyArrayField(ObjectType obj, List<NumpyArray<ArrayType>> value)Sets a numpy array value into a scikit-learn object. -
Uses of NumpyArray in ai.sklearn4j.naive_bayes
Methods in ai.sklearn4j.naive_bayes that return NumpyArray Modifier and Type Method Description NumpyArray<Double>BernoulliNaiveBayes. getClassLogPrior()Gets the log probability of each class (smoothed).NumpyArray<Double>CategoricalNaiveBayes. getClassLogPrior()Gets the log probability of each class (smoothed).NumpyArray<Double>ComplementNaiveBayes. getClassLogPrior()Gets the log probability of each class (smoothed).NumpyArray<Double>MultinomialNaiveBayes. getClassLogPrior()Gets the log probability of each class (smoothed).NumpyArray<Double>GaussianNaiveBayes. getClassPriors()Gets the class priors.NumpyArray<Double>ComplementNaiveBayes. getFeatureAll()Get the value of the feature_all_ field.NumpyArray<Double>BernoulliNaiveBayes. getFeatureCounts()Gets the number of samples encountered for each (class, feature) during fitting.NumpyArray<Double>ComplementNaiveBayes. getFeatureCounts()Gets the number of samples encountered for each (class, feature) during fitting.NumpyArray<Double>MultinomialNaiveBayes. getFeatureCounts()Gets the number of samples encountered for each (class, feature) during fitting.NumpyArray<Double>BernoulliNaiveBayes. getFeatureLogProbabilities()Gets the empirical log probability of features given a class, P(x_i|y).NumpyArray<Double>ComplementNaiveBayes. getFeatureLogProbabilities()Gets the empirical log probability of features given a class, P(x_i|y).NumpyArray<Double>MultinomialNaiveBayes. getFeatureLogProbabilities()Gets the empirical log probability of features given a class, P(x_i|y).NumpyArray<Double>GaussianNaiveBayes. getPriors()Gets the priors.NumpyArray<Double>GaussianNaiveBayes. getSigma()Gets the variance of the features.NumpyArray<Double>GaussianNaiveBayes. getTheta()Gets the mean of the features.protected abstract NumpyArray<Double>BaseNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>BernoulliNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>CategoricalNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>ComplementNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>GaussianNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>MultinomialNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.NumpyArray<Long>BaseNaiveBayes. predict(NumpyArray<Double> x)Perform classification on an array of test vectors X.NumpyArray<Double>BaseNaiveBayes. predictLogProbabilities(NumpyArray<Double> x)Return log-probability estimates for the test vector X.NumpyArray<Double>BaseNaiveBayes. predictProbabilities(NumpyArray<Double> x)Return probability estimates for the test vector X.Methods in ai.sklearn4j.naive_bayes that return types with arguments of type NumpyArray Modifier and Type Method Description List<NumpyArray<Double>>CategoricalNaiveBayes. getFeatureLogProbabilities()Gets the empirical log probability of features given a class, P(x_i|y).Methods in ai.sklearn4j.naive_bayes with parameters of type NumpyArray Modifier and Type Method Description protected abstract NumpyArray<Double>BaseNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>BernoulliNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>CategoricalNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>ComplementNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>GaussianNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.protected NumpyArray<Double>MultinomialNaiveBayes. jointLogLikelihood(NumpyArray<Double> x)Compute the unnormalized posterior log probability of X.NumpyArray<Long>BaseNaiveBayes. predict(NumpyArray<Double> x)Perform classification on an array of test vectors X.NumpyArray<Double>BaseNaiveBayes. predictLogProbabilities(NumpyArray<Double> x)Return log-probability estimates for the test vector X.NumpyArray<Double>BaseNaiveBayes. predictProbabilities(NumpyArray<Double> x)Return probability estimates for the test vector X.voidBernoulliNaiveBayes. setClassLogPrior(NumpyArray<Double> classLogPrior)Sets the log probability of each class (smoothed).voidCategoricalNaiveBayes. setClassLogPrior(NumpyArray<Double> classLogPrior)Sets the log probability of each class (smoothed).voidComplementNaiveBayes. setClassLogPrior(NumpyArray<Double> classLogPrior)Sets the log probability of each class (smoothed).voidMultinomialNaiveBayes. setClassLogPrior(NumpyArray<Double> classLogPrior)Sets the log probability of each class (smoothed).voidGaussianNaiveBayes. setClassPriors(NumpyArray<Double> classPriors)Sets the class priors.voidComplementNaiveBayes. setFeatureAll(NumpyArray<Double> featureAll)Sets the value of the value of the feature_all_ field.voidBernoulliNaiveBayes. setFeatureCount(NumpyArray<Double> featureCounts)Sets the number of samples encountered for each (class, feature) during fitting.voidComplementNaiveBayes. setFeatureCount(NumpyArray<Double> featureCounts)Sets the number of samples encountered for each (class, feature) during fitting.voidMultinomialNaiveBayes. setFeatureCount(NumpyArray<Double> featureCounts)Sets the number of samples encountered for each (class, feature) during fitting.voidBernoulliNaiveBayes. setFeatureLogProbabilities(NumpyArray<Double> featureLogProbabilities)Sets the empirical log probability of features given a class, P(x_i|y).voidComplementNaiveBayes. setFeatureLogProbabilities(NumpyArray<Double> featureLogProbabilities)Sets the empirical log probability of features given a class, P(x_i|y).voidMultinomialNaiveBayes. setFeatureLogProbabilities(NumpyArray<Double> featureLogProbabilities)Sets the empirical log probability of features given a class, P(x_i|y).voidGaussianNaiveBayes. setPriors(NumpyArray<Double> priors)Sets the priors.voidGaussianNaiveBayes. setSigma(NumpyArray<Double> sigma)Sets the variance of the features.voidGaussianNaiveBayes. setTheta(NumpyArray<Double> theta)Sets the mean of the features.Method parameters in ai.sklearn4j.naive_bayes with type arguments of type NumpyArray Modifier and Type Method Description voidCategoricalNaiveBayes. setFeatureLogProbabilities(List<NumpyArray<Double>> featureLogProbabilities)Sets the empirical log probability of 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Uses of NumpyArray in ai.sklearn4j.preprocessing.data
Methods in ai.sklearn4j.preprocessing.data that return NumpyArray Modifier and Type Method Description NumpyArrayRobustScaler. getCenter()Gets the The median value for each feature in the training set.NumpyArrayMinimumMaximumScaler. getDataMax()Gets the Per feature maximum seen in the dataNumpyArrayMinimumMaximumScaler. getDataMin()Gets the Per feature minimum seen in the dataNumpyArrayMinimumMaximumScaler. getDataRange()Gets the Per feature range `(data_max_ - data_min_)` seen in the dataNumpyArrayMaximumAbsoluteScaler. getMaxAbs()Gets the Per feature maximum absolute value.NumpyArray<Double>StandardScaler. getMean()Gets the The mean value for each feature in the training set.NumpyArrayMinimumMaximumScaler. getMin()Gets the Per feature adjustment for minimum.NumpyArray<Long>StandardScaler. getNSamplesSeen()Gets the The number of samples processed by the estimator for each feature.NumpyArrayMaximumAbsoluteScaler. getScale()Gets the Per feature relative scaling of the data.NumpyArrayMinimumMaximumScaler. getScale()Gets the Per feature relative scaling of the data.NumpyArrayRobustScaler. getScale()Gets the The (scaled) interquartile range for each feature in the training set.NumpyArray<Double>StandardScaler. getScale()Gets the Per feature relative scaling of the data to achieve zero mean and unit variance.NumpyArray<Double>StandardScaler. getVariance()Gets the The variance for each feature in the training set.NumpyArray<Double>Binarizer. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>MaximumAbsoluteScaler. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>MinimumMaximumScaler. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>Normalizer. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>RobustScaler. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>StandardScaler. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>Binarizer. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>MaximumAbsoluteScaler. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>MinimumMaximumScaler. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>Normalizer. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>RobustScaler. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>StandardScaler. transform(NumpyArray<Double> array)Takes the input array and transforms it.Methods in ai.sklearn4j.preprocessing.data with parameters of type NumpyArray Modifier and Type Method Description NumpyArray<Double>Binarizer. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>MaximumAbsoluteScaler. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>MinimumMaximumScaler. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>Normalizer. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>RobustScaler. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.NumpyArray<Double>StandardScaler. inverseTransform(NumpyArray<Double> array)Takes a transformed array and reveres the transformation.voidRobustScaler. setCenter(NumpyArray value)Sets the The median value for each feature in the training set.voidMinimumMaximumScaler. setDataMax(NumpyArray value)Sets the Per feature maximum seen in the datavoidMinimumMaximumScaler. setDataMin(NumpyArray value)Sets the Per feature minimum seen in the datavoidMinimumMaximumScaler. setDataRange(NumpyArray value)Sets the Per feature range `(data_max_ - data_min_)` seen in the datavoidMaximumAbsoluteScaler. setMaxAbs(NumpyArray value)Sets the Per feature maximum absolute value.voidStandardScaler. setMean(NumpyArray<Double> value)Sets the The mean value for each feature in the training set.voidMinimumMaximumScaler. setMin(NumpyArray value)Sets the Per feature adjustment for minimum.voidStandardScaler. setNSamplesSeen(NumpyArray<Long> value)Sets the The number of samples processed by the estimator for each feature.voidMaximumAbsoluteScaler. setScale(NumpyArray value)Sets the Per feature relative scaling of the data.voidMinimumMaximumScaler. setScale(NumpyArray value)Sets the Per feature relative scaling of the data.voidRobustScaler. setScale(NumpyArray value)Sets the The (scaled) interquartile range for each feature in the training set.voidStandardScaler. setScale(NumpyArray<Double> value)Sets the Per feature relative scaling of the data to achieve zero mean and unit variance.voidStandardScaler. setVariance(NumpyArray<Double> value)Sets the The variance for each feature in the training set.NumpyArray<Double>Binarizer. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>MaximumAbsoluteScaler. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>MinimumMaximumScaler. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>Normalizer. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>RobustScaler. transform(NumpyArray<Double> array)Takes the input array and transforms it.NumpyArray<Double>StandardScaler. transform(NumpyArray<Double> array)Takes the input array and transforms it. -
Uses of NumpyArray in ai.sklearn4j.preprocessing.label
Methods in ai.sklearn4j.preprocessing.label that return NumpyArray Modifier and Type Method Description NumpyArray<Long>LabelBinarizer. transform(List<Object> array)Takes the input array and transforms it.NumpyArray<Long>LabelEncoder. transform(List<Object> array)Transform labels to normalized encoding.NumpyArray<Long>MultiLabelBinarizer. transform(List<Set<Object>> array)Takes the input array and transforms it.Methods in ai.sklearn4j.preprocessing.label with parameters of type NumpyArray Modifier and Type Method Description List<Object>LabelBinarizer. inverseTransform(NumpyArray<Long> array)Takes a transformed array and reveres the transformation.List<Object>LabelEncoder. inverseTransform(NumpyArray<Long> array)Takes a transformed array and reveres the transformation.List<Set<Object>>MultiLabelBinarizer. inverseTransform(NumpyArray<Long> array)Takes a transformed array and reveres the transformation. -
Uses of NumpyArray in ai.sklearn4j.utils
Methods in ai.sklearn4j.utils that return NumpyArray Modifier and Type Method Description static NumpyArray<Double>Preprocessings. binarizeInput(NumpyArray<Double> x, double threshold)Binarize a numpy array based on a given threshold.static NumpyArray<Double>ExtMath. dot(NumpyArray<Double> v1, NumpyArray<Double> v2)Dot product of the NumpyArray.static NumpyArray<Double>ExtMath. rowNorm(NumpyArray<Double> x)Row-wise (squared) Euclidean norm of X.static NumpyArray<Double>ExtMath. rowNorm(NumpyArray<Double> x, boolean squared)Row-wise (squared) Euclidean norm of X.Methods in ai.sklearn4j.utils with parameters of type NumpyArray Modifier and Type Method Description static NumpyArray<Double>Preprocessings. binarizeInput(NumpyArray<Double> x, double threshold)Binarize a numpy array based on a given threshold.static NumpyArray<Double>ExtMath. dot(NumpyArray<Double> v1, NumpyArray<Double> v2)Dot product of the NumpyArray.static NumpyArray<Double>ExtMath. rowNorm(NumpyArray<Double> x)Row-wise (squared) Euclidean norm of X.static NumpyArray<Double>ExtMath. rowNorm(NumpyArray<Double> x, boolean squared)Row-wise (squared) Euclidean norm of X.
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