You can implement a simple linear SVM with numpy only like below. BTW, please google before you ask question next time. There are lots of resources and tutorial online. import numpy as np def my_svm(dataset, label): rate = 1 # rate for gradient descent epochs = 10000 # no of iterations weights = np.zeros(dataset.shape[1]) # … Read more
For starters, try detecting faces using vision.CascadeObjectDetector in the Computer Vision System Toolbox. If you have to roll your own, then take a look at this example, showing how to train a classifier to recognize digits using HOG features and SVM. Note, that the classifier is only one part of the process. You would need … Read more
You’re asking what ML representation you should use for user-classification of chat text. bag-of-words and word-vector are the main representations generally used in text-processing. However user-classification of chat is not the usual text-processing task, we look for telltale features indicative of a specific user. Here are some: character length, word length, sentence length of each … Read more
This question is about how to use these matlab functions: http://www.mathworks.com.au/help/stats/svmtrain.html http://www.mathworks.com.au/help/stats/svmclassify.html http://www.mathworks.com.au/help/bioinfo/ref/classperf.html If you are trying to classify entire videos you will have one label per video, i.e. assign 1 or 0 to “single block of 40 by 5 like 20 rows”, In which case your Training data matrix should be 20×200 (20 videos … Read more