From 8a705193ea4a58576de8cb66f7abb6e09724b679 Mon Sep 17 00:00:00 2001
From: Suyash Dongre <109069262+Suyashd999@users.noreply.github.com>
Date: Fri, 3 Nov 2023 23:32:16 +0530
Subject: [PATCH] Added doctest to decision_tree.py

---
 machine_learning/decision_tree.py | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/machine_learning/decision_tree.py b/machine_learning/decision_tree.py
index 7cd1b02c4181..8ec17d1cd4e4 100644
--- a/machine_learning/decision_tree.py
+++ b/machine_learning/decision_tree.py
@@ -49,6 +49,26 @@ def train(self, x, y):
         The contents of y are the labels for the corresponding X values
 
         train does not have a return value
+
+        Examples:
+        1. Try to train when x & y are of same length & 1 dimesions (No errors)
+        >>> dt = DecisionTree()
+        >>> dt.train(np.array([10,20,30,40,50]),np.array([0,0,0,1,1]))
+
+        2. Try to train when x is 2 dimesions
+        >>> dt = DecisionTree()
+        >>> dt.train(np.array([[1,2,3,4,5],[1,2,3,4,5]]),np.array([0,0,0,1,1]))
+        Error: Input data set must be one dimensional
+
+        3. Try to train when x and y are not of same length
+        >>> dt = DecisionTree()
+        >>> dt.train(np.array([1,2,3,4,5]),np.array([[0,0,0,1,1],[0,0,0,1,1]]))
+        Error: X and y have different lengths
+
+        4. Try to train when x & y are of same length but diffetent dimesions
+        >>> dt = DecisionTree()
+        >>> dt.train(np.array([1,2,3,4,5]),np.array([[1],[2],[3],[4],[5]]))
+        Error: Data set labels must be one dimensional
         """
 
         """