@@ -1,4 +1,5 @@
from sklearn.neighbors import NearestNeighbors, KNeighborsClassifier
+from sklearn.ensemble import RandomForestClassifier
import numpy as np
import sys
from Vector import *
@@ -23,6 +24,8 @@ def main():
print(classifcations)
print(newtest)
kNearestNeighbors(newdata, classifcations, newtest)
+ # print("Random Forest:")
+ # randomForest(newdata, classifcations, newtest)
# kNearestNeighbors([[1, 1, 0], [1, 0, 0], [0, 0, 0], [0, 5, 5]], ["three", 2, 3, "5"], [[1, 1, 0], [0, 5, 5]])
@@ -52,5 +55,11 @@ def nearestNeighbors(data: list, test_data: list):
return indicies, dist
+def randomForest(data: list, classifications: list, test_data: list):
+ rfc = RandomForestClassifier(n_estimators=len(data))
+ rfc.fit(data, classifications)
+ print(rfc.predict(test_data))
+
if __name__ == '__main__':
main()