Code for Python digit recognizer starter comptetition. http://www.kaggle.com/c/digit-recognizer
benchmark kNN k=10, cover_tree gives 0.96557 accuracy benchmark rf 1000 trees gives 0.96829 accuracy
knnpy-knn/experiment2 gives same accuracy as benchmark, but if we reduce dimmensions with PCA to lets say ~100 components kNN performs better than rf benchmark.
plotted explained variance of PCA helps to choose optimal component count to keep 90% variance
For kNN experiments
For random forests experiments
- numpy
- scipy
- sklearn (scikit-learn)
- matplotlib ======= kaggle ======
Kaggle - Machine Learning
bb025f0fd8de4d42be1320120b61fd32953dbd52