README.md

ML Regression Algorithms

Simple python implementation of various ML regression algorithms.

Requirements

• python
• numpy
• pandas
• matplotlib
• mpl_toolkits

1. Linear regression

code file: 1_linear_regression.py

data file: data.xlsx

Linear regression algorithm to estimate the weight parameters for the feature matrix (X) and the class label vector (y). Data file used for this experiment is data.xlsx - the first two columns are features and last columns is label (continous values)

2. Linear regression with stochastic gradient

code file: 2_linear_regression_stochastic.py

data file: data.xlsx

Linear regression with stochastic gradient and various plots of cost functions vs other parameters

3. Ridge regression with both batch gradient descent and stochastic gradient descent

code file: 3_ridge_regression.py

data file: data.xlsx

Ridge regression with both batch gradient descent and stochastic gradient descent. And various plots of cost functions vs other parameters in each case.

4. Least angle regression with both batch gradient descent and stochastic gradient descent

code file: 4_least_angle_regression.py

data file: data.xlsx

Least angle regression with both batch gradient descent and stochastic gradient descent. And various plots of cost functions vs other parameters in each case.

License

Distributed under the MIT License. See LICENSE.txt for more information.