[0.4.5] - 2026-06-17

Added

• Spearman correlation diagnostic attributes, populated automatically by fit():
  • recency_corr_ / frequency_corr_: equal-weight Spearman correlation between the RF rank
    and the empirical probability. Negative recency / positive frequency correlation indicates
    the expected monotonic relationship.
  • recency_corr_weighted_ / frequency_corr_weighted_: sample-size weighted variants.
  • recency_corr_pvalue_ / frequency_corr_pvalue_: two-sided p-values for the equal-weight
    correlations.
  • recency_slice_corr_ / frequency_slice_corr_: dicts of per-slice correlations for
    diagnosing 2D monotonicity (e.g. recency-vs-probability within each frequency level).
• verbose parameter to optimize() (default False): when True, prints solver progress and
  result summary.
• path parameter to plot_probability_surface() and plot_marginal_probability(): save the
  figure directly. A directory path writes a default filename
  (surface_{kind}_probability.png / marginal_{kind}_probability.png); a file path writes that
  name. Both methods now also show a default title based on kind when title=None.
• Practical tutorial notebooks (examples/tutorial_practical_ja.ipynb /
  tutorial_practical_en.ipynb): user-level train/test split, building all nine models,
  accuracy comparison, and model save/load (pickle and zip archive).

Changed

• show() redesigned as a structured diagnostic report (data statistics, fit parameters,
  Spearman correlations, and the empirical probability table) instead of the previous
  profiling-style output.
• plot_marginal_probability() API redesign. Breaking changes:
  • kind values changed from ("emp", "er", "ef", "mr", "mf", "all") to
    ("er", "ef", "mr", "mf", "rboth", "fboth"). The "all" overlay is split into "rboth"
    (empirical + monotonic recency) and "fboth" (empirical + monotonic frequency); "emp" is
    removed.
  • The axis parameter is removed (the axis is now inferred from kind).
  • The separate recency_label / frequency_label parameters are consolidated into a single
    axis_label=None.
• export_probability_csv(): the default output filename changed from {kind}_probability.csv
  to probability_{kind}.csv (e.g. probability_emp.csv). Breaking only for callers relying
  on the auto-generated name when passing path=None or a directory; explicit file paths are
  unaffected. (The CSV names inside the save_zip() archive are unchanged.)
• Internal aggregation dicts renamed to private:
  R/F/RF2N/RF2CV/RF2Prob/R2N/R2CV/R2Prob/F2N/F2CV/F2Prob → _R/_F/_RF2N/…. These were
  implementation details, not public API; the public probability attributes
  (emp_probability_dict_, er_probability_dict_, etc.) are unchanged.
• Documentation overhaul across docs/: document titles renamed (アーキテクチャ構成書 /
  機能仕様書 / リポジトリ構成 / 用語集), glossary.md restructured (基本概念・期間とデータ分割・
  アルゴリズム・API 簡潔版) with terminology unification (推薦スコア＝商品選択確率, 対象イベント,
  behavior history), and a release procedure added to development-guidelines.md.
• Beginner tutorial notebooks (tutorial_beginner_ja.ipynb / tutorial_beginner_en.ipynb)
  updated for the revised API and terminology.
• Test suite expanded (+30 cases; 439 passing) covering transform with 2D optimized kinds,
  plot path saving, objective-function fit quality (analytic optima), datetime64 splits, and
  version-mismatch semantics for load() / load_zip().

Removed

• recency_probability_ and frequency_probability_ attributes; consolidated into
  er_probability_ / ef_probability_.
• axis parameter, and the "emp" / "all" kind values, from plot_marginal_probability().

Fixed

• Dependency floor: cvxpy>=1.3 → cvxpy>=1.5. The optimizer explicitly solves with the
  CLARABEL solver, which is bundled with cvxpy since 1.4 and the default since 1.5; the previous
  >=1.3 floor could resolve an environment without CLARABEL available.