Move python files to root folder; remove built docs

miplearn/components/__init__.py

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+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.
+
+
+def classifier_evaluation_dict(tp, tn, fp, fn):
+    p = tp + fn
+    n = fp + tn
+    d = {
+        "Predicted positive": fp + tp,
+        "Predicted negative": fn + tn,
+        "Condition positive": p,
+        "Condition negative": n,
+        "True positive": tp,
+        "True negative": tn,
+        "False positive": fp,
+        "False negative": fn,
+        "Accuracy": (tp + tn) / (p + n),
+        "F1 score": (2 * tp) / (2 * tp + fp + fn),
+    }
+
+    if p > 0:
+        d["Recall"] = tp / p
+    else:
+        d["Recall"] = 1.0
+
+    if tp + fp > 0:
+        d["Precision"] = tp / (tp + fp)
+    else:
+        d["Precision"] = 1.0
+
+
+    t = (p + n) / 100.0
+    d["Predicted positive (%)"] = d["Predicted positive"] / t
+    d["Predicted negative (%)"] = d["Predicted negative"] / t
+    d["Condition positive (%)"] = d["Condition positive"] / t
+    d["Condition negative (%)"] = d["Condition negative"] / t
+    d["True positive (%)"] = d["True positive"] / t
+    d["True negative (%)"] = d["True negative"] / t
+    d["False positive (%)"] = d["False positive"] / t
+    d["False negative (%)"] = d["False negative"] / t
+    return d