Gradient boosting is an ensemble technique using which multiple weak learners can be ensembled to create a stronger prediction model. These weak learners are decision trees. And these decision trees are used sequentially so that one decision tree can be built based on...
If we are given a dataset, then we need to split the dataset into training and test sets before we run a machine learning model on the dataset. The machine learning model is then trained using the training set. And the test set is used to measure the performance of...
The contingency matrix is a simple and powerful metric using which we can measure the clustering performance in machine learning. A contingency matrix is an nxn matrix, where n is the number of clusters. A number ith row and jth column indicates the number of clusters...
What is the V-measure in clustering? The V-measure is a metric that can measure the clustering performance in machine learning. In our previous articles, we discussed what completeness score (What is completeness score?) and homogeneity score (What is homogeneity...
What is the homogeneity score in machine learning? The homogeneity score is a metric using which we can measure clustering performance in machine learning. A clustering result is said to be homogeneous if it contains data points that are members of a single class. A...
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