- Not recommend to write own code of learning algorithm. almost none of scientist nowaday code its own inverse matrices, multiply, and code its own SVM
- Sometimes SVM considered by many as Large Margin Classifier
- Supervised learning : no matter what algorithm, more importance is get lot of data, and choosing wisely which features to be incoporated, regularization etc.
- Previous: Precision & Recall as evaluation metrices to analyze learning algorithm with skew classes (data)
Previous: error analysis, single row number of error metrics to tell how well its doing
- Skewed classes: a somewhat trickier problem to handle with error analysis.