Recently I have studied k-nearest neighbour and decision trees and I am quite curious about the difference between the two,i.e,for task like seperating a target function \"return 1 if x2>x1,return 0 o
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I\'m curious about how works feature on many social sites today. For exa开发者_StackOverflowmple, you enter list of movies you like and system suggests other movies you may like (based on movies that
I want to know if I build up a decision tree A like ID3 from training and validation set,but A is unpruned.
I have a little app that mines data on social networks and returns interesting results (e.g. the latest conversations around a certain topic). However, the front end requires that the users开发者_运维
I\'m working on a cluster analysis program that takes a set of points S as an input and labels each point with that index of the cluster it belong to. I\'ve implemented the DBScan and OPTICS algorithm
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I wonder what is the best way to sample,say, 1000 questions,completely randomly from Yahoo! Answer. I want to achieve this complete randomness in which I will totally ignore the categories o开发者_如何
now I have a seemingly easy but challenging task.I need to develop a data set of questions,and I classify the questions into two categories:
I\'m trying to calculate how good are my measurements in machine learning! Let\'s say that I have five choices, and that error is 4,2, 0.002, 3, 6. Naturally, I will pick third one for the hit, but I
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