A class that implements Multilinear Regression for predicting values based on multiple features.
More...
#include <MultiLinearRegression.hpp>
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| | MultilinearRegression (double learningRate=0.01, int iterations=1000, double regularizationParameter=0.0) |
| | Constructs the MultilinearRegression model with the given learning rate and number of iterations. More...
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| void | train (const std::vector< std::vector< double >> &features, const std::vector< double > &target) |
| | Trains the Multilinear Regression model on the provided data. More...
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| double | predict (const std::vector< double > &features) const |
| | Predicts the output for a given set of features. More...
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| std::vector< double > | getWeights () const |
| | Gets the current weights of the model. More...
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| double | getBias () const |
| | Gets the current bias of the model. More...
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A class that implements Multilinear Regression for predicting values based on multiple features.
◆ MultilinearRegression()
| MultilinearRegression::MultilinearRegression |
( |
double |
learningRate = 0.01, |
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int |
iterations = 1000, |
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double |
regularizationParameter = 0.0 |
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) |
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inline |
Constructs the MultilinearRegression model with the given learning rate and number of iterations.
- Parameters
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| learningRate | The rate at which the model learns (default 0.01). |
| iterations | The number of iterations for the gradient descent (default 1000). |
| regularizationParameter | The regularization parameter lambda (default 0.0, no regularization). |
◆ getBias()
| double MultilinearRegression::getBias |
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| ) |
const |
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inline |
Gets the current bias of the model.
- Returns
- The bias term.
◆ getWeights()
| std::vector<double> MultilinearRegression::getWeights |
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| ) |
const |
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inline |
Gets the current weights of the model.
- Returns
- A vector containing the weights.
◆ predict()
| double MultilinearRegression::predict |
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const std::vector< double > & |
features | ) |
const |
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inline |
Predicts the output for a given set of features.
- Parameters
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| features | A vector containing feature values for a single data point. |
- Returns
- The predicted value.
◆ train()
| void MultilinearRegression::train |
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const std::vector< std::vector< double >> & |
features, |
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const std::vector< double > & |
target |
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) |
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inline |
Trains the Multilinear Regression model on the provided data.
- Parameters
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| features | A vector of vectors, where each sub-vector represents the features for one data point. |
| target | A vector containing the target values corresponding to each data point. |
- Exceptions
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| std::invalid_argument | If the number of features does not match the target size. |
The documentation for this class was generated from the following file:
