Bayes classificator
Plugging gaussian distro into bayes formula and taking logarithm leads to discriminant score Apply softmax to go from disc scores back to probability P(Y = k | X = x)
Evaluation of classifiers
Confusion matrix
- easy
- Bad for skewed and imbalanced distributions
RECALL = Accuracy, Specificity, Sensitivity
Sensitivity = TP / P 1 - Specificity = FP / N
Parameters Threshold -
ROC
- receiving operator characteristics 1 is good Steep is good
Classifiers comparasion
| Name | Assumptions | K | Good when |
|---|---|---|---|
| Logistic | 2 | ||
| Naive bayes | High dimension | ||
| LDA | reasonable gaussian | ||
| QDA | |||
| kNN | none, robust |
I’ve got that poisson
A ha! That poisson on my mind
probability something happens k times over fixed period of time or space
- Probability I’ll get fucked k times in a month (close to 0)
Only one parameter, nice
Generalized linear models
- Linear predictor + Link function + particular distribution
Party killer = particular
Exponential distribution family