types of regression analysis

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Types of Regression Analysis
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Table Of Content
4. Lasso Regression
1. Linear Regression
2. Logistic Regression
5. Polynomial Regression
3. Ridge Regression
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1.Linear Regression
Linear regression is one of the types of
regression analysis in machine learning. Linear
regression sample consists of a predictor
variable and a conditional variable related
linearly to individually different.
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2. Logistic Regression
Logistic regression analysis is the type of
regression analysis used to ensure the dependent
variable is discrete. (for example true or
false) it means a target variable can have just
two values the sigmoid arc indicates the
connection between the target variable and an
independent variable.
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3. Ridge Regression
Ridge Regression analysis type in machine
learning. It is usually used for the very high
correlation between the separate variables. In
the case of multi-collinear data, the shortest
square estimations provide fair values. While if
the collinear is high, it can be some bias
value. Accordingly, a bias matrix is introduced
by the Ridge Regression.
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4. Lasso Regression
Lasso Regression analysis in machine learning
helps regularization along with quality
selections. It prohibits the final size of the
regression analysis coefficient. as per the
outcome, a coefficient value reaches zero.
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5. Polynomial Regression
Polynomial Regression analysis is the exact as
Multiple Linear Regression with a bit of
modification polynomial regression analysis, a
connection between separate and dependent
variables.
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