{"id":143695,"date":"2024-12-07T18:22:23","date_gmt":"2024-12-07T12:52:23","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=143695"},"modified":"2026-06-01T14:40:39","modified_gmt":"2026-06-01T09:10:39","slug":"machine-learning-tennis-game-in-decision-tree","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/machine-learning-tennis-game-in-decision-tree\/","title":{"rendered":"Machine Learning Project \u2013 Tennis Game in Decision Tree"},"content":{"rendered":"<h3>Program 1<\/h3>\n<p><a href=\"https:\/\/drive.google.com\/file\/d\/1H2jZej_n39vTX3TOIZcCadf8Q9JzAUme\/view?usp=drive_link\" target=\"_blank\" rel=\"noopener\"><strong>Tennis Dataset<\/strong><\/a><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">import pandas as pd\r\nimport numpy as np\r\nfrom sklearn import tree\r\nfrom sklearn.preprocessing import LabelEncoder\r\n\r\n\r\ndf_tennis=pd.read_csv(\"D:\/\/scikit_data\/tennisData\/tennis.csv\")\r\n\r\ndf_tennis\r\n\r\n\r\ndf_tennis.shape\r\n\r\n\r\ndf_tennis.info()\r\n\r\n\r\ndf_tennis.isnull().sum()\r\n\r\n\r\ndf_tennis\r\n\r\n\r\n# Label Encoding \r\nle=LabelEncoder()\r\ndf_tennis['outlook_new']=le.fit_transform(df_tennis['outlook'])\r\ndf_tennis['temp_new']=le.fit_transform(df_tennis['temp'])\r\ndf_tennis['humidity_new']=le.fit_transform(df_tennis['humidity'])\r\ndf_tennis['windy_new']=le.fit_transform(df_tennis['windy'])\r\ndf_tennis['play_new']=le.fit_transform(df_tennis['play'])\r\n\r\n\r\n\r\ndf_tennis\r\n\r\n\r\ndf_tennis=df_tennis.drop(['outlook','temp','humidity','windy','play'],axis='columns')\r\n\r\n \r\ndf_tennis\r\n\r\n\r\n# Independed Variables(input)\r\ndf_input=df_tennis.drop('play_new',axis='columns')\r\n\r\n\r\ndf_input\r\n\r\n\r\n# Depended Variables\r\ndf_output=df_tennis.drop(['outlook_new','temp_new','humidity_new','windy_new'],axis='columns')\r\n\r\n\r\ndf_output\r\n\r\n\r\n# Model Predication\r\nmodel=tree.DecisionTreeClassifier()\r\ntype(model)\r\n\r\n\r\n# Train \r\nmodel.fit(df_input,df_output)\r\n\r\n\r\nmodel.predict([[0,1,0,0]])\r\n\r\n\r\nmodel.score(df_input,df_output)\r\n\r\nout1=int(input(\"Enter out look Weather(overcast-0,rainy-1,sunny-2) :\"))\r\ntemp1=int(input(\"Enter Temperature(cool-0,hot-1,mild-2):\"))\r\nhum1=int(input(\"Enter Humidity:(high-0,normal-1)\"))\r\nwend1=int(input(\"Enter windy or not(TRUE-1,FALSE-0) :\"))\r\nresult=model.predict([[out1,temp1,hum1,wend1]])\r\nif(result==1):\r\n    print(\"********PLayer Played a Tennis Game*******\")\r\nelse:\r\n    print(\".......Player does not Played a Tennis Game.....\")\r\n<\/pre>\n<p>&nbsp;<span hidden class=\"__iawmlf-post-loop-links\" data-iawmlf-links=\"[{&quot;id&quot;:2647,&quot;href&quot;:&quot;https:\\\/\\\/drive.google.com\\\/file\\\/d\\\/1H2jZej_n39vTX3TOIZcCadf8Q9JzAUme\\\/view?usp=drive_link&quot;,&quot;archived_href&quot;:&quot;&quot;,&quot;redirect_href&quot;:&quot;&quot;,&quot;checks&quot;:[],&quot;broken&quot;:false,&quot;last_checked&quot;:null,&quot;process&quot;:&quot;done&quot;}]\"><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Program 1 Tennis Dataset import pandas as pd import numpy as np from sklearn import tree from sklearn.preprocessing import LabelEncoder df_tennis=pd.read_csv(&#8220;D:\/\/scikit_data\/tennisData\/tennis.csv&#8221;) df_tennis df_tennis.shape df_tennis.info() df_tennis.isnull().sum() df_tennis # Label Encoding le=LabelEncoder() df_tennis[&#8216;outlook_new&#8217;]=le.fit_transform(df_tennis[&#8216;outlook&#8217;]) df_tennis[&#8216;temp_new&#8217;]=le.fit_transform(df_tennis[&#8216;temp&#8217;]) df_tennis[&#8216;humidity_new&#8217;]=le.fit_transform(df_tennis[&#8216;humidity&#8217;]) df_tennis[&#8216;windy_new&#8217;]=le.fit_transform(df_tennis[&#8216;windy&#8217;])&#46;&#46;&#46;<\/p>\n","protected":false},"author":581,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36],"tags":[8431,33127,33128,20697,33251,33252,33254,33253,33255],"class_list":["post-143695","post","type-post","status-publish","format-standard","hentry","category-machine-learning","tag-machine-learning","tag-machine-learning-practical","tag-machine-learning-program","tag-machine-learning-project","tag-machine-learning-tennis-game-in-decision-tree","tag-machine-learning-tennis-game-project","tag-tennis-game","tag-tennis-game-in-decision-tree","tag-tennis-game-project"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - 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DataFlair","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/data-flair.training\/blogs\/machine-learning-tennis-game-in-decision-tree\/","og_locale":"en_US","og_type":"article","og_title":"Machine Learning Project \u2013 Tennis Game in Decision Tree - DataFlair","og_description":"Program 1 Tennis Dataset import pandas as pd import numpy as np from sklearn import tree from sklearn.preprocessing import LabelEncoder df_tennis=pd.read_csv(\"D:\/\/scikit_data\/tennisData\/tennis.csv\") df_tennis df_tennis.shape df_tennis.info() df_tennis.isnull().sum() df_tennis # Label Encoding le=LabelEncoder() df_tennis['outlook_new']=le.fit_transform(df_tennis['outlook']) df_tennis['temp_new']=le.fit_transform(df_tennis['temp']) df_tennis['humidity_new']=le.fit_transform(df_tennis['humidity']) df_tennis['windy_new']=le.fit_transform(df_tennis['windy'])&#46;&#46;&#46;","og_url":"https:\/\/data-flair.training\/blogs\/machine-learning-tennis-game-in-decision-tree\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2024-12-07T12:52:23+00:00","article_modified_time":"2026-06-01T09:10:39+00:00","author":"DataFlair Team","twitter_card":"summary_large_image","twitter_creator":"@DataFlairWS","twitter_site":"@DataFlairWS","twitter_misc":{"Written by":"DataFlair Team","Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/data-flair.training\/blogs\/machine-learning-tennis-game-in-decision-tree\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/machine-learning-tennis-game-in-decision-tree\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/c187795dc82ab948373cca526df7c445"},"headline":"Machine Learning Project \u2013 Tennis Game in Decision Tree","datePublished":"2024-12-07T12:52:23+00:00","dateModified":"2026-06-01T09:10:39+00:00","mainEntityOfPage":{"@id":"https:\/\/data-flair.training\/blogs\/machine-learning-tennis-game-in-decision-tree\/"},"wordCount":12,"commentCount":0,"publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"keywords":["machine learning","machine learning practical","machine learning program","machine learning project","machine learning tennis game in decision tree","machine learning tennis game project","tennis game","tennis game in decision tree","tennis game project"],"articleSection":["Machine Learning Tutorials"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/data-flair.training\/blogs\/machine-learning-tennis-game-in-decision-tree\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/data-flair.training\/blogs\/machine-learning-tennis-game-in-decision-tree\/","url":"https:\/\/data-flair.training\/blogs\/machine-learning-tennis-game-in-decision-tree\/","name":"Machine Learning Project \u2013 Tennis Game in Decision Tree - 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