Here X is a vector (features of an example), W are the weights (vector of parameters) that determine how each feature affects the prediction andb is bias term. So our task T is to predict y from X, now we need to measure performance P to know how well the model performs. In 1967, the “nearest neighbor” algorithm was designed which marks the beginning of basic pattern recognition using computers. The program will use whatever data points are provided to describe each input object and compare the values to data about objects that it has already analyzed.
In this article, we describe both the potential that AI offers to automate aspects of care and some of the barriers to rapid implementation of AI in healthcare. Part of the art of choosing features is to pick a minimum set of independent variables that explain the problem. If two variables are highly correlated, either they need to be combined into a single feature, or one should be dropped. Sometimes people perform principal component analysis to convert correlated variables into a set of linearly uncorrelated variables. Since I mentioned feature vectors in the previous section, I should explain what they are. First of … Read More
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