USING K-NN to CLASSIFY CiFAR-10 Dataset

Performed k-Nearest neighbours clustering algorithm on the CiFAR-10 dataset to classify test images. Also performed k-fold cross validation to find the best value of the 'k' hyper parameter and best accuracy on the dataset.

Requirements

numpy matplotlib Python version 3.5 or later

References

The concepts used for this were derived from: -CS231n Convolutional Neural Netwroks for Visual Recognition -TensorFlow tutorials

Results

The dataset was subsampled to prevent memory issues and only 10000 training samples and 1000 testing sampleds were used; the results from k-NN classification are:

• Best k = 10
• Accuracy = 57%