36 lines
1.2 KiB
C
36 lines
1.2 KiB
C
/*
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logistic_regression.h
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---------------------
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Cost function and gradient for multinomial logistic regression model.
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Multinomial logistic regression is a generalization of regular logistic
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regression in which we predict a probability distribution over classes using:
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exp(x_i) / sum(exp(x))
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This is sometimes referred to as the softmax function and thus the model
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may be called softmax regression.
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*/
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#ifndef LOGISTIC_REGRESSION_MODEL_H
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#define LOGISTIC_REGRESSION_MODEL_H
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#include <stdio.h>
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#include <stdlib.h>
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#include <stdint.h>
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#include <stdbool.h>
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#include "collections.h"
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#include "matrix.h"
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#include "sparse_matrix.h"
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bool logistic_regression_model_expectation(matrix_t *theta, sparse_matrix_t *x, matrix_t *p_y);
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double logistic_regression_cost_function(matrix_t *theta, sparse_matrix_t *x, uint32_array *y, matrix_t *p_y, double lambda);
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bool logistic_regression_gradient(matrix_t *theta, matrix_t *gradient, sparse_matrix_t *x, uint32_array *y, matrix_t *p_y, double lambda);
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bool logistic_regression_gradient_sparse(matrix_t *theta, matrix_t *gradient, sparse_matrix_t *x, uint32_array *y, matrix_t *p_y,
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uint32_array *x_cols, double lambda);
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#endif
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