All functions
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auto_grouping()
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Reduce cardinality in categorical variable by automatic grouping |
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categ_analysis()
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Profiling analysis of categorical vs. target variable |
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compare_df()
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Compare two data frames by keys |
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concatenate_n_vars()
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Concatenate 'N' variables |
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convert_df_to_categoric()
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Convert every column in a data frame to character |
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coord_plot()
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Coordinate plot |
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correlation_table()
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Get correlation against target variable |
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cross_plot()
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Cross-plotting input variable vs. target variable |
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data_country
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People with flu data |
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data_golf
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Play golf |
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data_integrity()
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Data integrity |
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data_integrity_model()
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Check data integrity model |
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desc_groups()
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Profiling categorical variable |
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desc_groups_rank()
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Profiling categorical variable (rank) |
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df_status()
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Get a summary for the given data frame (o vector). |
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discretize_df()
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Discretize a data frame |
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discretize_get_bins()
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Get the data frame thresholds for discretization |
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discretize_rgr()
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Variable discretization by gain ratio maximization |
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entropy_2()
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Computes the entropy between two variables |
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equal_freq()
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Equal frequency binning |
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export_plot()
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Export plot to jpeg file |
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fibonacci()
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Fibonacci series |
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freq()
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Frequency table for categorical variables |
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funModeling-package
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funModeling: Exploratory data analysis, data preparation and model performance |
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gain_lift()
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Generates lift and cumulative gain performance table and plot |
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gain_ratio()
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Gain ratio |
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get_sample()
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Sampling training and test data |
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hampel_outlier()
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Hampel Outlier Threshold |
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heart_disease
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Heart Disease Data |
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infor_magic()
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Computes several information theory metrics between two vectors |
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information_gain()
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Information gain |
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metadata_models
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Metadata models data integrity |
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plot_num()
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Plotting numerical data |
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plotar()
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Correlation plots |
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prep_outliers()
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Outliers Data Preparation |
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profiling_num()
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Profiling numerical data |
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range01()
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Transform a variable into the [0-1] range |
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status()
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Get a summary for the given data frame (o vector). |
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tukey_outlier()
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Tukey Outlier Threshold |
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v_compare()
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Compare two vectors |
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var_rank_info()
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Importance variable ranking based on information theory |