added hyperopt space sample

cdplib/hyperopt/space_sample.py

@@ -0,0 +1,40 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Oct  5 09:50:24 2020
+
+@author: tanya
+"""
+
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.feature_selection import SelectPercentile
+from sklearn.linear_model import LogisticRegression
+from sklearn.decomposition import PCA
+from sklearn.pipeline import Pipeline
+from sklearn.preprocessing import StandardScaler
+from hyperopt import hp
+import numpy as np
+
+
+space = hp.choice("pipelines", [
+
+        {"name": "std_scaler_kbest_rf",
+         "pipeline": Pipeline([
+                 ("std_scaler", StandardScaler()),
+                 ("kbest", SelectPercentile()),
+                 ("rf", RandomForestClassifier())]),
+         "params": {"kbest__percentile":
+                    hp.choice('kbest__percentile', range(1, 3)),
+                    "rf__n_estimators":
+                    50 + hp.randint('rf__n_estimators', 50)}},
+
+        {"name": "std_scaler_pca_lr",
+         "pipeline": Pipeline([
+                 ("std_scaler", StandardScaler()),
+                 ("pca", PCA()),
+                 ("lr", LogisticRegression())]),
+         "params": {"lr__C":
+                    hp.loguniform("lr__C", np.log(0.01), np.log(0.1)),
+                    "pca__n_components":
+                    1 + hp.randint("pca__n_components", 4)}}
+        ])