Simple tips of Machine Learning
2018-03-04
Tips of Machine Learning
Data
- Quantity
- Representation
- Quality
- outliers
- missing features
- Irrelevant Features
- Feature selection
- Feature extraction
- Creating new features by gathering new data
Algorithm
- Overfitting: too complex relative to the amount and noisiness of the training data.
- regularization
- simplify the model
- reducing the number of attributes
- gather more training data
- reduce noise
- Underfitting
- more complex model
- better features
- reducing the regularization
Testing and Validating
- training set <–> validating set -finally-> testing set
- cross-validation
If you make absolutely no assumption about data,then there is no reason to prefer one model over any other. - No Free Lunch, David Wolpert