Implementation of Deep Neural Networks for data mining class of CS, SCUT.
Support for any structure of classification problems. You Just need apply a wee adjustment in load_data.py for some other dataset.
The dataset we use is dataset, from http://archive.ics.uci.edu/ml/index.php
The network is implemented by Keras.
After training process, the pro will output Learning Curve, save as save.jpg at the root. Like following:
Update: Update all implementaions of the ten methods. Include:
1. LDA
2. Support vector maching
3. Nearest Neighbors
4. Naive Bayes
5. Decision Trees
6. CART (Same implemention with Decision tree)
7. Random Forest
8. Adaboost
9. Gradient Tree Boosting
10. LabelPropagation and LabelSpreading