Applying PCA and t-SNE on images and visualizing Using Python 3. In this we will first take 2 images and Normalize the data We will put them in a pandas dataframe with 5 features x,y,r,g,b. The x and y features are the position of the pixel relative to the top left most pixel of the image. The r,g and b stand for the rgb values of the pixel. the data is normalised. We run a PCA and find the most significant components. The 3 most significant components are then plotted. Then we run t-SNE on the same normalized data with n = 2 components for 3 different perplexities(5,30,50).
abdulrehman1997 / applying-pca-and-t-sne-on-images-and-visualizing Goto Github PK
View Code? Open in Web Editor NEWApplying PCA and t-SNE on images and visualizing Using Python 3. In this we will take 2 images and Normalize the data