The goal of any machine learning problem is to find a single model that will best predict our wanted outcome. Rather than making one model and hoping this model is the best/most accurate predictor we can make, ensemble methods take a myriad of models into account, and average those models to produce one final model. It is important to note that Decision Trees are not the only form of ensemble methods, just the most popular and relevant in DataScience today.
  The people who work in Data Science and are busy finding the answers for different questions every day comes across the Data Science Methodology. Data Science Methodology indicates the routine for finding solutions to a specific problem. This is a cyclic process that undergoes a critic behaviour guiding business analysts and data scientists to act accordingly.     Business Understanding: Before solving any problem in the Business domain it needs to be understood properly. Business understanding forms a concrete base, which further leads to easy resolution of queries. We should have the clarity of what is the exact problem we are going to solve.  Analytic Understanding: Based on the above business understanding one should decide the analytical approach to follow. The approaches can be of 4 types: Descriptive approach (current status and information provided), Diagnostic approach(a.k.a statistical analysis, what is happening and why it is happening), Predictive approach(it forecasts on...

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