Checking Accuracy of Regression Algorithm.

There are five techniques of regression metrics to check the accuracy of regression algorithm(Loss function).

1.MAE

In mean absolute error we calculate the mean error.

The graph of mean absolute error is not differentiable.

2. MSE

Mean squared error fulfill the drawback of mean absolute error as its graph is differentiable.

In mean squared error rather than using the modulus function we calculate the square of all the errors.

Mean squared error is not robust to outliers.

3. RMSE

RMSE gives the root of the mean squared error.

It's properties are same as the mean squared error.

4. R2 Score

R2 Score calculates the difference between the mean line and the regression line.

R2 Score calculates the variance in percentage in our data set.

The biggest drawback of R2 score is when irrelevant columns are added the R2 score increases.

5. Adjusted R2 Score

Adjusted R2 Score fulfill the drawback of R2 Score. As it does not increase when is irrelevant columns are added.

Comments

Welcome to the Digital Era!!!

As we all know we are living in a Digital Era. Almost everything around us is digitally connected. For example, QR code. Almost everyone uses QR Code for financial transactions in there day to day life. If you see any business that is not on the internet it's like they are missing out on the digital world. No business can grow immensely without creating its digital presence. What is Digital Transformation? Digital transformation is the process of using digital technologies to transform existing traditional and non-digital business processes and services, or creating new ones, to meet with the evolving market and customer expectations, thus completely altering the way businesses are managed and operated, and how value is delivered to customers. To help you stay ahead of the game, we've compiled some of the most valuable insights from today's leading digital businesses. Some of Indian Startups bloom after Digital Transformation : 1. Lenskart Have you ever thought that you do

Ridge Regression Machine Learning

Bias variance trade off Bias means the inability of a machine learning model to truly capture the relationship in the training data set. That means it cannot understand the pattern in the training data set. Variance is the different of fits on different data sets. The difference between the training and the testing data set is variance. Overfitting When your data set works well on the trading data set but does not perform well on testing data set its called over fitting. Underfitting When your model does not perform well on your training data set then it is called under fitting. There are three methods for controlling over fitting: 1. Regularization 2. Bagging 3. Boosting There are 3 techniques of regularization: 1. Ridge Regression In this we add some more regularization terms to reduce the over fitting. Basically it's lambda. For performing ridge Regression we have an in-built class Ridge in sklearn Library. Let's see the code : from sklearn.linear_model import LinearRegress

Top 10 business ideas

Top 10 business ideas Hey do you want to become an self made entrepreneur? Do you want to start your own business? If yes then you are at the right place !!! The rise of entrepreneurship in India is unstoppable, and that is something we should be proud of.The wave of entrepreneurship is on it's hype. Here are some business ideas to bloom your career. 1. Online Reselling If you’re interested in clothing and/or sales, you might consider starting an online reseller business . Y ou can start your business as a side hustle and turn it into a full-time resale business. Here's your action plan: Choose the right type of reselling business. Identify the industry for your business. Identify the market and target audience for your business. Check out your competitors. Check if the business is viable. Start your reseller business online. 2. Professional Organizing If you’re a highly organized person who enjoys making spaces functional and comfortable, you might be good at coaching ot

Machine Learning Algorithm

Search This Blog