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dm:start:guidelines [29/09/2017 alle 09:56 (7 anni fa)] Anna Monreale [Guidelines for the task on Association Rules Mining] |
dm:start:guidelines [23/11/2020 alle 10:34 (3 anni fa)] (versione attuale) Riccardo Guidotti [Guidelines for the task on Classification] |
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====== Guidelines for the task on Data Understanding ====== | ====== Guidelines for the task on Data Understanding ====== | ||
* Data understanding (30 points) | * Data understanding (30 points) | ||
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- | * Distribution of the variables and statistics (7 points) | + | - Distribution of the variables and statistics (7 points) |
- | * Assessing data quality (missing values, outliers) (7 points) | + | - Assessing data quality (missing values, outliers) (7 points) |
- | * Variables transformations (6 points) | + | - Variables transformations (6 points) |
- | * Pairwise correlations and eventual elimination of redundant variables (7 points) | + | - Pairwise correlations and eventual elimination of redundant variables (7 points) |
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====== Guidelines for the task on Association Rules Mining ====== | ====== Guidelines for the task on Association Rules Mining ====== | ||
- | * Frequent patterns extraction with different values of support and different types (i.e. frequent, close maximal), (5 points) | + | * Frequent patterns extraction with different values of support and different types (i.e. frequent, close, maximal), (6 points) |
- | * Discussion of the most interesting frequent patterns (6 points) | + | * Discussion of the most interesting frequent patterns |
- | * Association rules extraction with different values of confidence (5 points) | + | * Association rules extraction with different values of confidence (6 points) |
- | * Discussion of the most interesting rules (6 points) | + | * Discussion of the most interesting rules and analyze how changes the number of rules w.r.t. the min_conf parameter, histogram of rules' confidence and lift (7 points) |
- | * Use the most meaningful rules to replace missing values and evaluate the accuracy | + | * Use the most meaningful rules to replace missing values and evaluate the accuracy (2 points) |
- | * Use the most meaningful rules to predict | + | * Use the most meaningful rules to predict |
====== Guidelines for the task on Classification ====== | ====== Guidelines for the task on Classification ====== | ||
- | * Learning of different decision trees with different parameters and gain formulas with the object of maximizing the performances (12 points) | + | * Learning of different decision trees/ |
- | * Decision trees interpretation (6 points) | + | * Decision trees interpretation, validation with test and training set (6 points) |
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* Discussion of the best prediction model (6 points) | * Discussion of the best prediction model (6 points) | ||