3. An ensemble refers to a group of machine learning based classifiers that are formed to...

 

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3. An ensemble refers to a group of machine learning based classifiers that are formed to classify new data points by taking a vote of their prediction as shown in Figure 1.0. As shown in Figure 1.0, the classifiers operate at the same time once they receive the input. To form an ensemble, the available options of classifiers consist of three (3) evolutionary algorithms, five (5) neural networks and four (4) support vector machines with different architectures. a. Input C. Classifier 1 Classifier 2 0 0 Classifier L OL Ensemble strategy Figure 1.0: An Ensemble If you need to form an ensemble consisting of six (6) classifiers, how many different ensembles can be formed? [2 marks] b. How many different ensembles if the ensemble must have six (6) classifiers and have equal number of classifiers from evolutionary algorithms, neural networks and support vector machines? [3 marks] The ensemble must consists of six (6) classifiers and all neural networks are used to form it. How many different ensembles are there? Ensemble output [3 marks] of six (6) [5 marks] d. How many different ensembles can be formed if the ensemble must consists classifiers and at least two (2) of the classifiers must be neural networks? 3. An ensemble refers to a group of machine learning based classifiers that are formed to classify new data points by taking a vote of their prediction as shown in Figure 1.0. As shown in Figure 1.0, the classifiers operate at the same time once they receive the input. To form an ensemble, the available options of classifiers consist of three (3) evolutionary algorithms, five (5) neural networks and four (4) support vector machines with different architectures. a. Input C. Classifier 1 Classifier 2 0 0 Classifier L OL Ensemble strategy Figure 1.0: An Ensemble If you need to form an ensemble consisting of six (6) classifiers, how many different ensembles can be formed? [2 marks] b. How many different ensembles if the ensemble must have six (6) classifiers and have equal number of classifiers from evolutionary algorithms, neural networks and support vector machines? [3 marks] The ensemble must consists of six (6) classifiers and all neural networks are used to form it. How many different ensembles are there? Ensemble output [3 marks] of six (6) [5 marks] d. How many different ensembles can be formed if the ensemble must consists classifiers and at least two (2) of the classifiers must be neural networks?