- Classification
- Clustering
- Sequence Pattern
https://github.com/rushter/MLAlgorithms
https://github.com/eriklindernoren/ML-From-Scratch
- bikin time measurement per algoritma
- Classification
- KNN
- SVM
- Random Forest
- Clustering
- K means
- SpectralClustering
- Hierarchical Clustering
- Sequence Pattern
- Cari library
- Prefix Span
- Generalized Sequence Pattern
- Laporan ipnyb
- Exploratory Data Analysis
- Performance Analysis per algoritma
https://github.com/Jean-njoroge/Breast-cancer-risk-prediction
Jadi biar lebih seru, urutan dari x_train dan x_Test di shuffle pake sklearn.utils.shuffle. Lalu dibandingkan dengan data asli
- 19 Epoch, 4 Layer (memakai adam optimiser, backprop)
31 23 17 13 (input_nodes: train_X.shape, hidden_nodes1: input_nodes, hidden_nodes2, hidden_nodes3)
Epoch: 0 Accuracy: 0.62719 Cost: 303.86292 Valid Accuracy: 0.60714 Valid Cost: 37.30396
Epoch: 1 Accuracy: 0.63158 Cost: 274.62439 Valid Accuracy: 0.60714 Valid Cost: 33.73276
Epoch: 2 Accuracy: 0.69956 Cost: 224.27368 Valid Accuracy: 0.62500 Valid Cost: 27.30453
Epoch: 3 Accuracy: 0.86842 Cost: 172.38452 Valid Accuracy: 0.87500 Valid Cost: 21.12439
Epoch: 4 Accuracy: 0.93860 Cost: 138.36185 Valid Accuracy: 0.89286 Valid Cost: 17.99998
Epoch: 5 Accuracy: 0.95614 Cost: 110.83379 Valid Accuracy: 0.91071 Valid Cost: 14.10146
Epoch: 6 Accuracy: 0.96930 Cost: 77.26272 Valid Accuracy: 0.94643 Valid Cost: 8.75187
Epoch: 7 Accuracy: 0.97149 Cost: 55.30008 Valid Accuracy: 0.98214 Valid Cost: 4.56376
Epoch: 8 Accuracy: 0.97807 Cost: 41.37629 Valid Accuracy: 1.00000 Valid Cost: 2.64346
Epoch: 9 Accuracy: 0.97588 Cost: 37.30238 Valid Accuracy: 1.00000 Valid Cost: 1.97846
Epoch: 10 Accuracy: 0.97807 Cost: 34.33464 Valid Accuracy: 1.00000 Valid Cost: 1.60540
Epoch: 11 Accuracy: 0.97588 Cost: 33.48156 Valid Accuracy: 1.00000 Valid Cost: 1.33480
Epoch: 12 Accuracy: 0.97588 Cost: 29.47034 Valid Accuracy: 1.00000 Valid Cost: 1.19615
Epoch: 13 Accuracy: 0.98684 Cost: 31.13475 Valid Accuracy: 1.00000 Valid Cost: 1.16577
Epoch: 14 Accuracy: 0.98684 Cost: 26.50785 Valid Accuracy: 1.00000 Valid Cost: 1.20009
Epoch: 15 Accuracy: 0.98904 Cost: 22.84942 Valid Accuracy: 1.00000 Valid Cost: 1.25582
Epoch: 16 Accuracy: 0.98684 Cost: 25.87312 Valid Accuracy: 1.00000 Valid Cost: 1.25636
Epoch: 17 Accuracy: 0.98684 Cost: 26.54008 Valid Accuracy: 1.00000 Valid Cost: 1.16558
Epoch: 18 Accuracy: 0.98684 Cost: 25.67315 Valid Accuracy: 1.00000 Valid Cost: 1.10405
Epoch: 19 Accuracy: 0.98684 Cost: 23.48993 Valid Accuracy: 1.00000 Valid Cost: 1.06180
Run Complete Finished.
