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By:
Sarah Grabow
- decks
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Decks in this class (23)
Basic Definitions
Target variable,
Predictor,
Continuous variable
18
cards
Exploratory Data Analysis
Exploratory data analysis,
Univariate numerical,
Bivariate numerical
4
cards
R notes
Library dplyr,
Combining levels,
Unique values
39
cards
Variable Transformations
Log transformations,
Numeric vs factor,
Dummy variables
4
cards
Modeling definitions
Modeling considerations before,
Modeling considerations during,
Modeling considerations after
11
cards
Model Accuracy - pt1
Model accuracy,
Model accuracy regression problems,
Model accuracy regression bias
8
cards
Model Accuracy pt 2
Model accuracy validation set,
Data partition seed,
Data partition stratified sampling
6
cards
MLR
Definition,
Model performance,
Notes
4
cards
MLR - model assumptions
Violations for mlr,
Vi,
2 heteroscedasticity
10
cards
Stepwise Selection
Information criteria,
Information criteria,
Model performance
7
cards
Regularization
Ridge regression,
Ridge regression,
Lasso regression
7
cards
GLM
Linear exponential family,
Linear exponential family,
Two modeling choices
10
cards
GLM - Continuous Target
Weights,
Other notes
2
cards
GLM - Binary Target
Bernoulli distribution,
Logistic regression
2
cards
GLM - Count Target
Exposures
1
cards
Decision Trees
Main idea,
Tree structure,
Tree flexibility
10
cards
Decision Trees - Regression Trees
Trees for continuous targets,
Poisson trees
2
cards
Decision Trees - Classification Trees
Trees for binary target,
Pruning,
Classification trees and target v...
3
cards
Ensemble Methods - Models
Random forests,
Random forests basics,
Boosting
6
cards
Ensemble Methods - Other Modeling Aspects
Binary target,
Oversampling,
Undersampling
4
cards
Principal Component Analysis
Main idea,
Notes,
Variance explained
6
cards
Clustering - k-means
Clustering,
K means clustering,
K means clustering notes
4
cards
Clustering - Hierarchical
Hierarchical clustering steps,
Hierarchical clustering notes,
Dendrogram notes
3
cards
More about
Exam PA
- Class purpose General learning
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