Predictive Power Score (PPS) analysis provides an asymmetric, data-type-agnostic score that can detect linear or non-linear relationships between variables. PPS ranges from 0 (no predictive power) to 1 (perfect predictive power).
Usage
jpps(
data,
analysis_type = "predictors",
target_var = NULL,
predictor_var = NULL,
predictor_vars = NULL,
matrix_vars = NULL,
algorithm = "auto",
cv_folds = 4,
sample_size = 5000,
show_heatmap = TRUE,
show_barplot = TRUE,
show_correlation_comparison = FALSE,
correlation_method = "pearson",
min_pps_threshold = 0,
sort_results = "pps_desc",
color_scheme = "viridis",
custom_color_low = "#FFFFFF",
custom_color_high = "#FF0000",
show_values_on_plot = TRUE,
plot_title = "",
show_summary = TRUE,
show_interpretation = TRUE
)Arguments
- data
Dataset for PPS analysis
- analysis_type
Type of PPS analysis to perform
- target_var
Target variable to predict (for single/predictors analysis)
- predictor_var
Single predictor variable (for single analysis)
- predictor_vars
Multiple predictor variables (for predictors analysis)
- matrix_vars
Variables to include in full PPS matrix
- algorithm
Machine learning algorithm for PPS calculation
- cv_folds
Number of cross-validation folds
- sample_size
Maximum sample size for analysis (0 = no limit)
- show_heatmap
Display PPS results as heatmap
- show_barplot
Display PPS scores as barplot
- show_correlation_comparison
Compare PPS with Pearson correlation
- correlation_method
Correlation method for comparison
- min_pps_threshold
Minimum PPS score to display in results
- sort_results
How to sort the results
- color_scheme
Color scheme for visualizations
- custom_color_low
Color for low PPS values (hex code)
- custom_color_high
Color for high PPS values (hex code)
- show_values_on_plot
Display PPS values on heatmap/barplot
- plot_title
Custom title for plots (auto-generated if empty)
- show_summary
Display summary of PPS analysis
- show_interpretation
Provide interpretation guidance for PPS results
Value
A results object containing:
results$instructions | a html | ||||
results$pps_scores | a table | ||||
results$correlation_comparison | a table | ||||
results$pps_heatmap | an image | ||||
results$pps_barplot | an image | ||||
results$comparison_plot | an image | ||||
results$summary_stats | a table | ||||
results$interpretation | a html |
Tables can be converted to data frames with asDF or as.data.frame. For example:
results$pps_scores$asDF
as.data.frame(results$pps_scores)