Machine Learning & Logistic Regression Quiz
Machine Learning & Logistic Regression Quiz
Test your knowledge in machine learning and logistic regression with our engaging quiz! Designed for enthusiasts and professionals alike, this quiz will help reinforce your understanding of key concepts and techniques in the field.
Participate to:
- Challenge yourself with 10 thought-provoking questions.
- Learn about classification algorithms and model building.
- Evaluate your grasp of statistical assumptions.
Machine Learning Classification Algorithm use to predict the probability of categorical dependent variables
Logistic
Simple
Multiple
Ridge and Lasso
Uses small amount of bias to reduce variance
Ridge
Lasso
Simple
Multiple
Assumptions of Logistic Regression (check if applicable)
Little to No Multicollinearity
Requires Large Sample Sizes
Independence of Errors
Factor Level 1 of Dependent Variable should represent the desired outcome
Independent Variable are Linearly related to log odds
Assumes residuals to be normally distributed
Linearity
Multivariate Normality
Lack of Multicollinearity
Homoscedasticity
What are the steps in building a mlr model
Identify Variables
Encode Categorical Data
Build Model
Check Assumptions
Create Dummy Variable
Avoid Dummy Variable Trap
Split Test/Training Sets
0 correlation means no correlation
True
False
Categorical Independent Data is also called Indicator Value
True
False
Overfitting is when the model performs well on test but fails on training
True
False
What is used to prevent overfitting
Regularization
Normalization
Bias
Covariance
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