Questions tagged [exploratory-factor-analysis]

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Performing EDA on a dataset with missing features

I'm new to DS. I want to perform EDA on such dataset, where these are the missing features stats of my train and test sets: train: Test_0 0 Test_1 31 Test_2 0 Test_3 141 ...
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Filling NaN values

According to my knowledge, before filling nan values we have to check whether data is missing because of MCAR, MAR or MNAR and it depends on how features are correlated with each other and then make a ...
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Industry analysis - multiple industries

I am trying to run logistic regression on marketing leads and use industry as a predictor of whether the lead converts (1/0). Often, when I enrich data from websites like crunchbase the associated ...
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How to predict strategy based on given data using Machine Learning? [closed]

My basic goal is to predict strategy based on given data for instance a) Predict what formation In a football match will maximize my winning rate b) Predict what product combination will maximize my ...
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Does the sign of correlation matter in feature selection?

If I understand correctly, the correlation between features and the target can be used to quantify whether those features are relevant to keep, hence the ritual of plotting the correlation matrix as a ...
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When would you use feature optimization method instead of exploratory analysis to identify best features?

I have a dataset with around 70 features. I'm currently just plotting graphs and trying to identify key information. I also wish to later do a predictive model. What would be the best way to get the ...
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Factor Analysis vs PCA

Could someone please explain when FA is used or when PCA is used, as I understood FA do dimensionality reduction, however PCA - the main goal is the same. Then which one should I use and in which ...
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Practical Interpretation of PCAs for a supplier analysis

I am using PCA to validate and research a set of 13 suppliers of products against a set of about 50 variables and performance indicators against an ideal "wish"-Supplier, mostly based on G. ...
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Creating sub categories

I have data we have collected quarterly over the last two years from two organisations. They are collected via the use of 29 questions. For each organisation, there are about 500 answers per question. ...
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Determine which factor is responsible for a change in a top-line business metric?

Are there any techniques for determining which factor(s) is (are) responsible for a change in a top-line business metric? E.g., revenue drops - but was it because of a drop in global visitors, or ...
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Why are correlation matrices used versus a matrix of R^2 values?

I'm relatively new to DS, so forgive me if this is a dumb question or in the wrong forum When evaluating features it seems that almost everywhere a correlation matrix is used ...
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Why is Regularization after PCA or Factor Analysis a bad idea?

I have done Factor Analysis on my data and applied various machine learning models on it. I particularly find it giving high MSE value for Ridge and Lasso Regression compared to other models. I want ...
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What conclusion can I get when the variable is influenced by other but there isn't any correlation?

I am doing an analytic exploratory analysis. If the target is a continuous variable and the attributes are all categorical (discrete values), in order to know if exist any influence on the target from ...
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Factor Analysis with Mixed Data Concurrent Approach with PCAmixdata in R

I am trying to perform Factor Analysis over Mixed Data using R with PCAmixdata package. My dataset is huge with almost 115000 records and almost 40 features of both categorical and continuous. When I ...
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SEM (Structural Equation Modelling) with Exploratory Factor Analysis

Problem Statement: I need to do some Structural Equation Modelling at work to get the main factors in a marketing survey data-set. There are no assumed equations to perform SEM on so what would be ...
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