Notebook Difficulty Level: ★★★☆☆
Previous Notebooks that are part of “Rock, Paper or Scissor Game – Train and Classify” module
- Rock, Paper or Scissor Game – Train and Classify [Volume 1] | Experimental Setup
- Rock, Paper or Scissor Game – Train and Classify [Volume 2] | Feature Extraction
- Rock, Paper or Scissor Game – Train and Classify [Volume 3] | Feature Selection
Following Notebooks that are part of “Rock, Paper or Scissor Game – Train and Classify” module
After the previous three volumes of the Jupyter Notebook dedicated to our “Classification Game”, we are reaching a decisive stage: Training of Classifier .
Currently, as demonstrated in the previous volume , all the training data (examples and respective features) are ready to be applied to a classification algorithm.
The choice of classification algorithm resulted in the selection of k-Nearest Neighbour classifier.
On current Jupyter Notebook it will be described relevant steps to achieve our goal of training a k-Nearest Neighbour classifier.
