We read every piece of feedback, and take your input very seriously. Include my email address so I can be contacted Cancel Submit feedback Saved searches Use saved searches to filter your results more quickly Cancel Create saved search Sign in Sign up Reseting focus {...
We read every piece of feedback, and take your input very seriously. Include my email address so I can be contacted Cancel Submit feedback Saved searches Use saved searches to filter your results more quickly Cancel Create saved search Sign in Sign up Reseting fo...
Qiu et al. [11] combined the particle swarm optimization algorithm with naive Bayes, which effectively reduced redundant attributes and improved the classification ability. Ramoni et al. [12] constructed a robust Bayes classifier (RBC) for datasets with missing values, which can handle incomplete ...
You can explore this optimization if you’re interested later. from math import sqrt # Calculate the standard deviation of a list of numbers def stdev(numbers): avg = mean(numbers) variance = sum([(x-avg)**2 for x in numbers]) / float(len(numbers)-1) return sqrt(variance) 1 2 3...
Search or jump to... Search code, repositories, users, issues, pull requests... Provide feedback We read every piece of feedback, and take your input very seriously. Include my email address so I can be contacted Cancel Submit feedback Saved searches Use saved searches to filter your...
This is illustrated in Figure 1. This becomes a constrained optimization problem which can be solved using Lagrange multipliers. Figure 1. An illustration of support vector machine (SVM) intuition. For a linearly separable data, a number of feature vectors z are given as inputs, 𝑀=(𝑥...