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Vishal Kapur
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Vishal Kapur's Discussions

Passing Nan values to ML Algorithm

Started this discussion. Last reply by Vishal Kapur Sep 19. 3 Replies

Suppose I have 10 independent variable, and I intentionally didn't remove the nan value from few of my independent variable and move it to numpy and then passed it to the ML algo. Will few of the…Continue

Input to PCA

Started this discussion. Last reply by Yassin Jomni Sep 8. 5 Replies

Suppose I have 20 independent vsariables and I am thinking to go for PCA, Do we need to do the scaling of all these 20 independent variable, or PCA will handle it... And I hope the output of PCA will…Continue

Feature Selection >> On Labelled Data..

Started this discussion. Last reply by Piyush Agarwal Jan 29. 4 Replies

I am working on a data set that has 10 features, and my label ed output is the 'Weight of humans'.I want to find, out of 10 features, which are he 2 or 3 features due to which the 'Weight' varies..…Continue

Missing Value in DATA - Approaches

Started this discussion. Last reply by Vishal Kapur Nov 4, 2018. 2 Replies

Hello Guys,I am new to ML and I am starting with Exploratory Data Analysis, need help on good material on graphs, statistical methods to use when we first see data, different approach to fill missing…Continue

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Latest Activity

Vincent Granville liked Vishal Kapur's discussion Input to PCA
Oct 8
Vishal Kapur's discussion was featured

Input to PCA

Suppose I have 20 independent vsariables and I am thinking to go for PCA, Do we need to do the scaling of all these 20 independent variable, or PCA will handle it... And I hope the output of PCA will be scaled features...See More
Oct 1
Vishal Kapur replied to Vishal Kapur's discussion Passing Nan values to ML Algorithm
"But NAN values, can't be handled by neural networks, if suppose we have few missing value in one of the features, neural network give NAN as output."
Sep 19
Yassin Jomni replied to Vishal Kapur's discussion Input to PCA
"The result of the PCA won't be normalized. PCA is an orthogonal linear transformation between your initial data space and a new space that is spanned by the eigenvectors of the covariance/correlation matrix. The only thing you could say is…"
Sep 8
Yassin Jomni replied to Vishal Kapur's discussion Input to PCA
"It depends. You can compute the PCA on two ways: 1- By computing the eigenvalues and eigenvectors of the covariance matrix: In this case, you need to normalize your data (between 0-1) 2- By computing the eigenvalues and eigenvectors of the…"
Sep 8
T. Dickinson replied to Vishal Kapur's discussion Input to PCA
"Scaling the input variables is your job as the analyst. Do you want to center and spherize the data? if so, center the data by subtracting the mean vector from all data vectors and sweep out the standard deviations. The result will be a mean vector…"
Sep 3
Vincent Granville liked Vishal Kapur's discussion Passing Nan values to ML Algorithm
Sep 1
Vishal Kapur replied to Vishal Kapur's discussion Passing Nan values to ML Algorithm
"Thanks..  but just for knowledge, like any algo, such as SVM or linear regression will give error, if I pass nan value.. "
Aug 29
Vincent Granville replied to Vishal Kapur's discussion Passing Nan values to ML Algorithm
"NaN stands for "not a number". If it is a missing value instead, some algorithms such as decision trees handle them automatically. See also imputation methods (google the term) to estimate what the value could have been. Now if it is truly…"
Aug 29
Vishal Kapur's discussion was featured

Passing Nan values to ML Algorithm

Suppose I have 10 independent variable, and I intentionally didn't remove the nan value from few of my independent variable and move it to numpy and then passed it to the ML algo. Will few of the algo give error. Can ML also such as (Decision tree, SVM etc) can handle nan value. If these ML algo doesn't give error, then how will these nan values will be treated/handled internally by the algo.See More
Aug 29
Vishal Kapur posted a discussion

Passing Nan values to ML Algorithm

Suppose I have 10 independent variable, and I intentionally didn't remove the nan value from few of my independent variable and move it to numpy and then passed it to the ML algo. Will few of the algo give error. Can ML also such as (Decision tree, SVM etc) can handle nan value. If these ML algo doesn't give error, then how will these nan values will be treated/handled internally by the algo.See More
Aug 29
Vishal Kapur replied to Vishal Kapur's discussion Input to PCA
"Thanks, but I want to know, do we need to do the scaling of data before PCA, so that all independent variable lies betwee 0 & 1??"
Aug 28
Jeremy Ireland replied to Vishal Kapur's discussion Input to PCA
"PCA is one approach to it, however, what is your main goal? If you want to reduce variables and group them into indices, PCA is an adequate approach. If you intend on using all 20 IVs, some form of linear/log regression may be best. Is this survey…"
Aug 28
Vishal Kapur's discussion was featured

Input to PCA

Suppose I have 20 independent vsariables and I am thinking to go for PCA, Do we need to do the scaling of all these 20 independent variable, or PCA will handle it... And I hope the output of PCA will be scaled features...See More
Aug 27
Vishal Kapur posted a discussion

Input to PCA

Suppose I have 20 independent vsariables and I am thinking to go for PCA, Do we need to do the scaling of all these 20 independent variable, or PCA will handle it... And I hope the output of PCA will be scaled features...See More
Aug 27
Vishal Kapur replied to Mirko Krivanek's discussion What will be the next big thing after data science?
"I think Quantum Computing will come next by 2023, to fuel the exponential growth of AI.."
Aug 27

Profile Information

Field of Expertise
Other
Professional Status
Technical
Years of Experience:
12
Industry:
Banking Technology
Your Job Title:
Software Developer
How did you find out about DataScienceCentral?
Google
Interests:
Contributing, Networking, Finding a new position

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