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Stochastic Gradient Descent for linear regression #15
To implement stochastic gradient descent to optimize a linear regression algorithm on Boston House Prices dataset which is already exists in sklearn as a sklearn.linear_model.SGDRegressor.here,SGD algorithm is defined manually and then comapring the both results.Linear regression is technique to predict on real values.
stochastic gradient descent technique , evaluates and updates the coefficients every iteration to minimize the error of a model on training data.
Objective:
To Implement stochastic gradient descent on Bostan House Prices dataset for linear Regression
Implement SGD and deploy on Bostan House Prices dataset.
Comapare the Results with sklearn.linear_model.SGDRegressor
Compare the results when Learning rate is constant
priyagunjate
commented
4 years ago
To implement stochastic gradient descent to optimize a linear regression algorithm on Boston House Prices dataset which is already exists in sklearn as a sklearn.linear_model.SGDRegressor.here,SGD algorithm is defined manually and then comapring the both results.Linear regression is technique to predict on real values.
stochastic gradient descent technique , evaluates and updates the coefficients every iteration to minimize the error of a model on training data.
Objective:
To Implement stochastic gradient descent on Bostan House Prices dataset for linear Regression