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Unsupervised-ML---Association-Rules-Data-Mining-Titanic. Data Preprocessing: As the data is categorical format, we are using One Hot Encoding to convert into numerical format. Apriori Algorithm: frequent item sets & association rules. A leverage value of 0 indicates independence. Range will be [-1 1]. A high conviction value means that the conse…

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P32.-Unsupervised-ML---Association-Rules-Data-Mining-Titanic-

Data Preprocessing: As the data is categorical format, we are using One Hot Encoding to convert into numerical format

Apriori Algorithm: frequent item sets & association rules. A leverage value of 0 indicates independence. Range will be [-1 1]. A high conviction value means that the consequent is highly depending on the antecedent and range [0 inf]. Lift Ratio > 1 is a good influential rule in selecting the associated transactions.

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Unsupervised-ML---Association-Rules-Data-Mining-Titanic. Data Preprocessing: As the data is categorical format, we are using One Hot Encoding to convert into numerical format. Apriori Algorithm: frequent item sets & association rules. A leverage value of 0 indicates independence. Range will be [-1 1]. A high conviction value means that the conse…

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