Data Classifier Assignment This is a solution of Vodafone Data Classifier Assignment which discuss data classifiers, poor customer support analysis and more.
Answer 1: 1. 2. 3.
ID’s in Category table shall be unique identifier to identify the correct issue category however it is not the case with the database provided. One ID is representing multiple issues categories. Vodafone customers are not only suffering from bad services but also from the poor customer support as well. Customers are not satisfied with the interactions, they are having with customer representatives. As per data analysis, issues with Vodafone are not only from new customers, but also from the customers who are associated with Vodafone from long and facing issues with Vodafone services.
Answer 2: The query used for merging the two tables is shown below: SELECT Category.[Issue Category], Comment FROM Category INNER JOIN Vodafail ON Category.ID = Vodafail.ID;
Answer 3: Output generated from query above (mentioned in Answer 2) will be used as an input File. This files contains data from both the tables provided in Vodafail database. As we require analysis to be done based on Issue Category and comments, we have selected these two attributes only while forming query to retrieve the data. Saved the output as Output.xlsx and then transform the data similar to “test.tab” so that I can use this data in Orange File widget. Earlier I get errors while loading this data which I have removed and data was successfully loaded in Orange using File Widget. Read about Computer Hardware Clock Assignment.
Answer 4: Data Classifier that I have used is Naïve Bayes and Interactive Tree Builder. Visualizer I use Attribute Statistics. Data Table I have used to visualize the data that I supplied using File widget. Naïve Bayes: is a classification technique, which is based on the Bayesian theorem and is particularly suited when the dimensionality of the inputs is high. Even though it is simple, Naive Bayes can often outperform more sophisticated classification methods. This widget provides output as learner and classifier.
Interactive Tree Builder: This is a very exciting widget which is useful for teaching induction of classification trees and also in practice, where a data miner and an area expert can use it to manually construct a classification tree. Attribute Statistics: Attribute Statistics shows distributions of attribute values. It is helpful to identify any anomalies in the data supplied. Read about Vodafone Test Learnerâ€™s Assignment. Screen shot of Orange schema designed is as given below:
Output screen shot for this schema is as given below:
Output screen shot of data visualizer is as given below:
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