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#Multicollinearity

Showing: 9 courses
NPTEL

Engineering Econometrics

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This course will be exclusively quantitative and an application to business/management-related problems. It is connected with problem sets and real-life cases to know the relevance of a particular problem and the decision-making thereof.
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61 Lesons
1 day 11 hours
On-Demand
Free-Video
NPTEL-NOC IITM

Classical Linear Regression Model - Part 4

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Explore advanced concepts in classical linear regression, focusing on model interpretation, diagnostics, and practical applications in statistical analysis.
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1 Lesons
28 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Classical Linear Regression Model - Part 3

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Explore advanced concepts of classical linear regression, including model assumptions, estimation techniques, and statistical inference for robust data analysis.
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1 Lesons
33 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Statistical Inference of Logistic Regression: Confusion Matrix, Errors, and Model Selection

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Explore statistical inference in logistic regression, covering confusion matrices, error types, and model selection techniques for improved predictive accuracy.
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8 Lesons
17 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Understanding Multicollinearity

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Explore multicollinearity and its impact on regression analysis, focusing on the Variance Inflation Factor as a key diagnostic tool.
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1 Lesons
18 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Classical Linear Regression Model - Part 2

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Explore advanced concepts of classical linear regression, including model assumptions, parameter estimation, and statistical inference techniques.
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1 Lesons
32 minutes
On-Demand
Free-Video
UofU Data Science

Principal Component Analysis and Singular Value Decomposition - Spring 2023

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Master dimensionality reduction techniques through PCA and SVD, exploring multicollinearity, vector basis, and practical applications with hands-on demonstrations for effective data analysis.
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16 Lesons
1 hour 23 minutes
On-Demand
Free-Video
CodeEmporium

Preprocessing Data for Machine Learning - Deep Dive

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Comprehensive guide to preprocessing data for logistic regression, covering standardization, encoding, data imbalance, correlation, multicollinearity, and missing data handling techniques.
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10 Lesons
20 minutes
On-Demand
Free-Video
NPTEL-NOC IITM

Handling Multicollinearity with Ridge Regression in Python

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Implement Ridge Regression using Python and sklearn to handle multicollinearity in data analysis.
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1 Lesons
18 minutes
On-Demand
Free-Video