Delete scikit-learn/SCIKIT-LEARN_USER_GUIDE.txt

scikit-learn/SCIKIT-LEARN_USER_GUIDE.txt

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-================================================================================
-  SCIKIT-LEARN - USER GUIDE (Android Python STB) - Generated by RIMI
-================================================================================
-
-What is scikit-learn?
----------------------
-scikit-learn is a Python module for machine learning built on top of SciPy
-(numpy, scipy) and distributed under BSD-3-Clause. It provides simple and
-efficient tools for predictive data analysis: classification, regression,
-clustering, dimensionality reduction, model selection, preprocessing.
-
-This wheel is cross-compiled for Android (cp312, android_24_x86_64 /
-android_24_arm64_v8a, 16KB page, NoRELRO, single libc++_shared.so).
-
-Installation
-------------
-Via PipManager in app or via Install_WHEELS_to_DEVICE.ps1 (option 1 ALL or 2 single):
-  pip install scikit_learn-1.7.1-cp312-cp312-android_24_x86_64.whl
-
-Requires at runtime (all in WHEELS, pure+native):
-  numpy>=1.22.0 (6.4M android_24_x86_64, 16KB)
-  scipy>=1.8.0 (31M android_24_x86_64, 16KB, no C: RUNPATH)
-  joblib>=1.2.0 (0.29M pure)
-  threadpoolctl>=3.1.0 (0.02M pure)
-
-No extra build deps needed at runtime (cython, meson-python only for building).
-
-Quick Start (Android)
----------------------
-import sklearn
-print(sklearn.__version__)  # 1.7.1
-
-from sklearn.datasets import load_iris
-X, y = load_iris(return_X_y=True)  # X shape (150,4)
-
-from sklearn.preprocessing import StandardScaler
-scaler = StandardScaler()
-Xt = scaler.fit_transform(X)
-
-from sklearn.decomposition import PCA
-pca = PCA(n_components=2)
-Xt2 = pca.fit_transform(X)  # shape (150,2)
-
-from sklearn.cluster import KMeans
-km = KMeans(n_clusters=3, n_init=10, random_state=42)
-labels = km.fit_predict(X)
-
-from sklearn.linear_model import LogisticRegression
-clf = LogisticRegression(max_iter=200)
-clf.fit(X[:100], y[:100])
-pred = clf.predict(X[:5])
-
-from sklearn.ensemble import RandomForestClassifier
-clf = RandomForestClassifier(n_estimators=10, random_state=42)
-clf.fit(X[:100], y[:100])
-
-from sklearn.metrics import accuracy_score
-acc = accuracy_score(y_true, y_pred)
-
-from sklearn.model_selection import train_test_split, cross_val_score
-Xtr, Xte, ytr, yte = train_test_split(X, y, test_size=0.25, random_state=42)
-scores = cross_val_score(clf, X, y, cv=3)
-
-API Gotchas (Android)
----------------------
-- All 69 Cython extensions are 16KB page aligned (LOAD 0x4000, no GNU_RELRO,
-  NEEDED libc++_shared.so only, no C: RUNPATH). Verified via llvm-readelf.
-- sklearn imports numpy/scipy/joblib/threadpoolctl — ensure those wheels
-  are installed first (Install_WHEELS_to_DEVICE.ps1 does it in sorted order).
-- No tkinter/matplotlib required for core; plotting via matplotlib is optional
-  (extra, not needed for ML).
-- For XGBoost sklearn interface (XGBRegressor/XGBClassifier), sklearn must be
-  installed (now in WHEELS 1.7.1, 7-8M).
-
-Tested Features (Test_ScikitLearn.py)
--------------------------------------
-- import sklearn, C extension _tree
-- load_iris, load_digits
-- StandardScaler, MinMaxScaler
-- PCA (10->2)
-- KMeans (3 clusters)
-- LogisticRegression, LinearRegression
-- RandomForestClassifier (10 trees)
-- accuracy_score, mean_squared_error
-- train_test_split, cross_val_score (3-fold)
-
-All 15 tests PASS, 0 SKIP, 0 FAIL on Android x86_64 emulator (Python 3.12.14).
-
-Platform Notes (Android)
-------------------------
-- Arch: x86_64 (emulator) and arm64-v8a (phone) — both 16KB, NoRELRO
-- NDK r26, clang 17.0.2, LLD, -z norelro -z max-page-size=16384
-- Links only to /data/app/.../lib/x86_64/libc++_shared.so (custom 1.3M, not NDK 4K)
-  + librimi.so + libpython3.12.so.1.0 — no libc++.so/libc++abi.so/libunwind.
-- No Windows C:/ paths in any .so (strings check 0).
-
-Troubleshooting
----------------
-- ImportError: No module named 'sklearn' → install wheel via PipManager
-- ImportError: libomp.so → already handled via threadpoolctl, no extra
-- If Test_ScikitLearn shows SKIP for missing joblib/threadpoolctl, install
-  those pure wheels first (they are in WHEELS).
-
-================================================================================
-  Generated by RIMI
-================================================================================