How regression applied in data science

read about logistic regression for free in just 3 minutes

Business Intelligence :

• Bi is widely used for price optimization and inventory management.
• In other words, this technique reduces costs and increases profits.

Traditional Methods :

• Also called predictive analytics, used for predicting future values with good accuracy.

Regression is a model used for describing relationship among variables in our analysis.

Logistic regression :

• Logistic regression is a non — linear model, values on the vertical line will be 1s and 0s
• Eg: like filtering job candidates, If selected means 1s otherwise rejected means 0s.

Cluster Analysis :

• This technique can be applied only when the data are divided into few groups.

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Factor Analysis :

• It Combines more variables into one.
• Grouping Explanatory variables together.
• It reduces dimensionality.

Time Series Analysis :

• Representation is always in a horizontal line.
• Variable are independent.
• This analysis is widely used for measuring Stock price.

Example: Sales Forecasting which uses Time Series Analysis.

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Read more articles :

How machine learning used in data science

The role of Business Intelligence in data science

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