From dbe1f6f0a2ce0d3ca0484e42cacbfa2cf7e90729 Mon Sep 17 00:00:00 2001
From: KirkDCO <rkdelisle@gmail.com>
Date: Wed, 15 May 2024 11:46:49 -0600
Subject: [PATCH] Add algorithm options of KNeighborRegressor/Classifier; Add
 SelectFdr to Selectors

---
 tpot/config/classifier.py | 10 +++++++++-
 tpot/config/regressor.py  | 10 +++++++++-
 2 files changed, 18 insertions(+), 2 deletions(-)

diff --git a/tpot/config/classifier.py b/tpot/config/classifier.py
index f720d850a..adc82550e 100644
--- a/tpot/config/classifier.py
+++ b/tpot/config/classifier.py
@@ -81,7 +81,8 @@
     'sklearn.neighbors.KNeighborsClassifier': {
         'n_neighbors': range(1, 101),
         'weights': ["uniform", "distance"],
-        'p': [1, 2]
+        'p': [1, 2],
+        'algorithm': ["kd_tree", "ball_tree"]  # using "brute" results in memory spikes
     },
 
     'sklearn.svm.LinearSVC': {
@@ -192,6 +193,13 @@
         }
     },
 
+    'sklearn.feature_selection.SelectFdr': {
+        'alpha': np.arange(0, 0.05, 0.001),
+        'score_func': {
+            'sklearn.feature_selection.f_classif': None
+        }
+    },
+
     'sklearn.feature_selection.SelectPercentile': {
         'percentile': range(1, 100),
         'score_func': {
diff --git a/tpot/config/regressor.py b/tpot/config/regressor.py
index 8e9d2eb78..af2df0899 100644
--- a/tpot/config/regressor.py
+++ b/tpot/config/regressor.py
@@ -69,7 +69,8 @@
     'sklearn.neighbors.KNeighborsRegressor': {
         'n_neighbors': range(1, 101),
         'weights': ["uniform", "distance"],
-        'p': [1, 2]
+        'p': [1, 2],
+        'algorithm': ["kd_tree", "ball_tree"]  # using "brute" results in memory spikes
     },
 
     'sklearn.linear_model.LassoLarsCV': {
@@ -186,6 +187,13 @@
         }
     },
 
+    'sklearn.feature_selection.SelectFdr': {
+        'alpha': np.arange(0, 0.05, 0.001),
+        'score_func': {
+            'sklearn.feature_selection.f_regression': None
+        }
+    },
+
     'sklearn.feature_selection.SelectPercentile': {
         'percentile': range(1, 100),
         'score_func': {