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Advanced Human-Machine Interaction Interaction Data Analysis TD03: Mining Sequences of Itemsets

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Advanced Human-Machine Interaction Interaction Data Analysis

TD03: Mining Sequences of Itemsets

INSA Rouen Normandie - Normandie University

TD Machine

1. Explore how to use the Apriori algorithm using Java using Weka (https://www.cs.waikato.ac.nz/

~ml/weka/) or in Python (e.g. apyori1.1.1).

2. Try to apply Apriori on the following data : https://storm.cis.fordham.edu/~gweiss/data-mining/

weka-data/weather.arff (or from Moodle). Why is this not possible ? Pre-process the data so that Apriori could be applied.

3. Using Apriori, identify :

the three best association rules (maximum condence and support) to predict a game (i.e. rules containing "play=yes") ;

the three best association rules (maximum condence and support) to predict the absence of a game (i.e. rules containing "play=no") ;

4. Use the sequence generator presented last week to generate new data that you could mine for the pre- diction of a particular context (e.g. item or item-set).

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