I am training a SVM classifier based on a given document collections. I started from using 500 documents for training, then I add another 500 for training, and so on. In other words, I have three training sets, 500, 1000, 1500. And the smaller training set is a subset of the sequential larger set. I … Read more
I have trained an linear SVM which takes a pair of objects, computes features and is expected to learn a semantic similarity function between objects(we can say that it predicts whether the two objects are similar enough that they should be merged or not). The problem I am facing is that the predictions can be … Read more
I recently learned about the use of the Kernel trick, which maps data into higher dimensional spaces in an attempt to linearize the data in those dimensions. Are there any cases where I should avoid using this technique? Is it just a matter of finding the right kernel function? For linear data this is of … Read more
I recently learned about the use of the Kernel trick, which maps data into higher dimensional spaces in an attempt to linearize the data in those dimensions. Are there any cases where I should avoid using this technique? Is it just a matter of finding the right kernel function? For linear data this is of … Read more
I am trying to plot the decision boundary of a One Class SVM. This is a 2 dimensional representation of my training data And here the picture of the prediction obtained on the training data How can you see the values seems to be assigned randomly. In theory I should obtain a ball that contains … Read more
I am trying to plot the decision boundary of a One Class SVM. This is a 2 dimensional representation of my training data And here the picture of the prediction obtained on the training data How can you see the values seems to be assigned randomly. In theory I should obtain a ball that contains … Read more
Disclaimer: I'm nearing the end introductory machine course so knowledge on the subject is not too strong (yet)! Context: I'm thinking of building an optical word search solver for a term project for the said class. The user will draw a box around the character matrix and then it's the job of the program to … Read more
I applied SVM to perform the classification against several data sets. It turns out that the performance metric of recall is pretty bad for one data set. It has recall around 50% while other data sets have recall around 80%. For this kind of scenario, what are the possible approaches that are available to improve … Read more
I applied SVM to perform the classification against several data sets. It turns out that the performance metric of recall is pretty bad for one data set. It has recall around 50% while other data sets have recall around 80%. For this kind of scenario, what are the possible approaches that are available to improve … Read more
I have learned that, when dealing with data using model-based approach, the first step is modeling data procedure as a statistical model. Then the next step is developing efficient/fast inference/learning algorithm based on this statistical model. So I want to ask which statistical model is behind the support vector machine (SVM) algorithm? Best Answer You … Read more