network_stuff:machine_learning:supervised_learning
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SUPERVISED LEARNING:
In python, we use the method fit to train a model. Fit~train
kmeans.fit(argument) kmeans.predict (argument) # ython predict() predicts the labels of the data values based on the trained model.
REGRESSION
For continuous tgt values
DECISON TRESS
- k-nearest neighbors
- ~ “classification by proximity” ; majority vote
- after doing it with all points, it creates a “boundary” (ie classification)
- decision trees
- decision by path to leaves ; measure of center
- we ask question to narrow down areas (normally y/n Qs)
- decision trees can surface relationships that were not evident for the human understanding.
- random forests(?)
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