Discussion 7
ManojMartha
LinearandLogisticsRegression.pptx
Simple Regression Model
Regression Analysis
Regression models (both linear and non-linear) are used for predicting a real value, like salary for example. If your independent variable is time, then you are forecasting future values, otherwise your model is predicting present but unknown values. Regression technique vary from Linear Regression to SVR and Random Forests Regression.
In this part, you will understand and learn how to implement the following Machine Learning Regression models:
Simple Linear Regression
Logistic Regression
Support Vector for Regression (SVR)
Decision Tree Classification
Linear Regression in R
Simple Linear Regression Use Cases
Real State
Demand forecasting:
Medical
Logistics Regression Model
Logistic Regression
Logistic Regression
Logistic Regression
Logistic Regression
Logistic Regression Plot
Use Cases
Medical
Finance
Marketing
Engineering
Discussion
Compare and contrast linear and logistic regression methods. Support your answer with use cases for each regression model
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