There are 16 classes to choose from. The training data includes images from each class. Your goal in training is to develop classification algorithms that can map images to the correct class label. The test data will only include images without labels. You can use confusion matrix and accuracy to report your results. After your final submission, your code will be run to confirm your results. Note that you are expected to do a comprehensive analysis by using multiple algorithms. You are not restricted to the algorithms studied in class.
For the evaluation, please download the sample file in csv format. The left column is for the test image number and the right column is for the predicted class labels (1-16). Please replace the right column by your predicted class labels and upload the file named as
"project_Image_fullname"