pca_experiment.ipynb experiments with PCA in generall. pca_dimreduct.ipynb fits a PCA model (on healthy data only) which is saved and later re-used as a dimensionality reduction method before the ...

To small number of hidden factors in a particular layer obviously results in insufficient learning. To help you to follow Autoencoder's logic in network building, let's talk about matching number 0 to ...

The high dimensionality and complex structure of DNA microarray data pose significant challenges for accurate cancer detection, as redundant and irrelevant features may lead to overfitting and reduced ...

Machine learning system for predicting profitable trades in high-frequency markets using ensemble models and dimensionality reduction. jane-street-prediction/ ├── src/jane_street/ │ ├── data/ │ │ └── ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation of a dataset that has fewer columns. Imagine that you have a dataset that has many ...