Index
A
- A/B testing, A/B Testing-For Further Reading
- control group, advantages of using, Why Have a Control Group?
- epsilon-greedy algorithm, Multi-Arm Bandit Algorithm
- importance of permissions, Why Just A/B? Why Not C, D…?
- traditional, shortcoming of, Multi-Arm Bandit Algorithm
- accuracy, Evaluating Classification Models
- improving in random forests, Random Forest
- Adaboost, Boosting
- boosting algorithm, The Boosting Algorithm
- adjusted R-squared, Assessing the Model
- adjustment of p-values, Multiple Testing, Multiple Testing
- agglomerative algorithm, The Agglomerative Algorithm
- AIC (Akaike's Information Criteria), Model Selection and Stepwise Regression, Selecting the Number of Clusters
- variants of, Model Selection and Stepwise Regression
- Akike, Hirotugu, Model Selection and Stepwise Regression
- all subset regression, Model Selection and Stepwise Regression
- alpha, Statistical Significance and P-Values, Alpha
- dividing up in multiple testing, Multiple Testing
- alternative hypothesis, Hypothesis Tests, Alternative Hypothesis
- American Statistical Association (ASA), statement on p-values, Value of the p-value
- anomaly detection, Outliers, Regression and Prediction
- ANOVA (analysis of variance
- statististical test based on F-statistic, F-Statistic
- ANOVA (analysis of variance), ANOVA-Further Reading
- computing ANOVA table in R, F-Statistic
- decomposition of variance, F-Statistic
- two-way, Two-Way ANOVA
- arms (multi-arm bandits), Multi-Arm Bandit Algorithm
- AUC (area under the ROC curve), AUC
- average linkage, Measures of Dissimilarity ...
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