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Avilash Ghosh
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Asked: November 4, 2021In: Linear Regression

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and win INR 5000 in 30mins! Register now! Register link: Read more

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Asked: July 8, 2021In: Linear Regression

Dropping of variables which are not significant and are having high VIF value

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For more accuracy while fitting a linear model, we drop the input variables/features which are not significant(i.e pvalue>0.05) and whose variation inflation factor is  greater  than 5,I have landed up in a case where both input variables are highly correlated ...Read more

For more accuracy while fitting a linear model, we drop the input variables/features which are not significant(i.e pvalue>0.05) and whose variation inflation factor is  greater  than 5,I have landed up in a case where both input variables are highly correlated with each other and significant too,so which one should I drop?

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mahima_vaidya
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Asked: July 5, 2021In: Python

Multiple Linear Regression

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If the p value of a specific independent variable is less than 0.05 then it is considered to be a statistically significant variable. How to extract these variables from the dataset using Python ?

If the p value of a specific independent variable is less than 0.05 then it is considered to be a statistically significant variable. How to extract these variables from the dataset using Python ?

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NehaSequeira
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Asked: June 17, 2021In: Linear Regression

Scaling for numeric variables

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Why is scaling for numeric variables done before splitting it into a train & test dataset?

Why is scaling for numeric variables done before splitting it into a train & test dataset?

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NehaSequeira
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Asked: June 16, 2021In: Linear Regression

Intercept in linear regression model

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Why do we need an intercept in a linear regression model? If we use statsmodel.OLS do we need to add the intercept explicitly and how do we do it?

Why do we need an intercept in a linear regression model?

If we use statsmodel.OLS do we need to add the intercept explicitly and how do we do it?

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Ketaki Bhide
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Asked: June 15, 2021In: Linear Regression

Linear regression with multiple variables

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I was working on Dataset of Insurance in Python it had both categorical and numeric variables. For fitting a linear regression model I did the conversion of categorical to dummy variable, did scaling of whole data frame afterwards, after splitting ...Read more

I was working on Dataset of Insurance in Python it had both categorical and numeric variables. For fitting a linear regression model I did the conversion of categorical to dummy variable, did scaling of whole data frame afterwards, after splitting training and testing data and, fitting model on training data, I found that VIF of one variable was more than 5 .(So while finding method, for reducing this high VIF, I came across Recursive Feature elimination method, in which it detects essential variables and nonessential variables). That particular variable with high VIF came under essential, so my query is should drop that variable by criteria of high VIF or keep it as it is? Is it only criteria for dropping variable?

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Rudrava Mukherjee
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Asked: February 20, 2021In: Logistic Regression

Constant in Logistic Regression

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Why do we need to add a constants column with the independent variables while doing logistic regression?

Why do we need to add a constants column with the independent variables while doing logistic regression?

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Aditya Sharma
Aditya Sharma

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Asked: January 27, 2021In: Linear Regression

P-Value in Linear Regression

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In Linear Regression, if the p-value of the f-stat is < 0.05 we reject the H0 and accept the Ha. Which means we know that at least one variable has a coefficient greater than zero. For individual variables, we consider ...Read more

In Linear Regression, if the p-value of the f-stat is < 0.05 we reject the H0 and accept the Ha. Which means we know that at least one variable has a coefficient greater than zero. For individual variables, we consider the variable to be statistically significant if the p-value<0.05. Why this is so?

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Bikash Ghosh
Bikash Ghosh

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Asked: January 26, 2021In: Linear Regression

Model Overfitting or Underfitting

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How do I know if my model is Overfitting or Underfitting?

How do I know if my model is Overfitting or Underfitting?

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Bikash Ghosh
Bikash Ghosh

Bikash Ghosh

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Asked: January 26, 2021In: Python

How can I validate user input in Python

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How can I make the program ask for valid inputs instead of crashing when non-sensible data is entered?

How can I make the program ask for valid inputs instead of crashing when non-sensible data is entered?

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    Dipayan Sarkar added an answer One of the assumptions of Linear Regression - No multicollinearity.… July 14, 2021 at 4:46 am
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    mahima_vaidya added an answer 'OLS' object has no attribute 'pvalues' This is the error… July 6, 2021 at 7:24 am
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    Dipayan Sarkar added an answer The statsmodels.regression.linear_model.OLSResults.pvalues should give you the pvalues of the respective… July 5, 2021 at 6:10 pm
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