shinshiner / Gene_Chip_Ananysis

Classification on gene chips

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Gene_Chip_Ananysis

Congratulations on your choice of a interesting course if you find this repository. Don't be tired of his f**g lectures, or you would be failed in the final exam...

Dataset

  • features: output/data/dataset_train.npy dataset_test.npy (3558 * num_of_features)
  • labels: output/data/target_train.npy dataset_test.npy (3558 * 1)

LR

using 1 fc-layer.

SVM

using 1 fc-layer and hinge loss.

NN

using several fc-layers and crossentropy loss.

Current accuracy (About 10-30 epochs)

  • LR: 88% (with l2 norm) 87% (without norm)
  • SVM: 89%
  • NN: 91% (with l2 norm, dropout(0.5), relu activation funciton)

Results could be improved with some more parameters adjustment.

About

Classification on gene chips


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Language:TeX 58.5%Language:Python 41.5%