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Expectation-Maximization AlgorithmĮxpectation-Maximization (EM) is used as a clustering algorithm, just like the k-means algorithm for knowledge discovery. Thought the algorithm is highly efficient, it consumes a lot of memory, utilizes a lot of disk space and takes a lot of time. Apriori algorithm is used for discovering interesting patterns and mutual relationships and hence is treated as an unsupervised learning approach. Once the association rules are learned, it is applied to a database containing a large number of transactions. Association rules are a data mining technique that is used for learning correlations between variables in a database. Apriori AlgorithmĪpriori algorithm works by learning association rules. Once projected, SVM defined the best hyperplane to separate the data into the two classes.
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SVM exaggerates to project your data to higher dimensions. A hyperplane is an equation for a line that looks something like “ y = mx + b”. SVM learns the datasets and defines a hyperplane to classify data into two classes. In terms of tasks, Support vector machine (SVM) works similar to C4.5 algorithm except that SVM doesn’t use any decision trees at all. As per standard implementations, k-means is an unsupervised learning algorithm as it learns the cluster on its own without any external information. It may not be guaranteed that group members will be exactly similar, but group members will be more similar as compared to non-group members. One of the most common clustering algorithms, k-means works by creating a k number of groups from a set of objects based on the similarity between objects. PG Diploma in Machine Learning & AI from IIIT-B and upGrad. Decision trees are always easy to interpret and explain making C4.5 fast and popular compared to other data mining algorithms. The training dataset is labelled with lasses making C4.5 a supervised learning algorithm. The decision tree created by C4.5 poses a question about the value of an attribute and depending on those values, the new data gets classified. Classifier here refers to a data mining tool that takes data that we need to classify and tries to predict the class of new data.Įvery data point will have its own attributes. C4.5 is used to generate a classifier in the form of a decision tree from a set of data that has already been classified. C4.5 AlgorithmĬ4.5 is one of the top data mining algorithms and was developed by Ross Quinlan. In the KNN algorithm, what is meant by underfitting?.What exactly does ‘K’ mean in the k-means algorithm?.
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