{"id":28114,"date":"2022-12-28T18:14:44","date_gmt":"2022-12-28T12:44:44","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-can-you-guys-help-me-by-telling-how-to-do-these-tasks-using-python-closed\/"},"modified":"2022-12-28T18:14:44","modified_gmt":"2022-12-28T12:44:44","slug":"solved-can-you-guys-help-me-by-telling-how-to-do-these-tasks-using-python-closed","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-can-you-guys-help-me-by-telling-how-to-do-these-tasks-using-python-closed\/","title":{"rendered":"[Solved] can you guys help me by telling how to do these tasks using python [closed]"},"content":{"rendered":"<p> [ad_1]<br \/>\n<\/p>\n<div id=\"answer-73488682\" class=\"answer js-answer accepted-answer js-accepted-answer\" data-answerid=\"73488682\" data-parentid=\"73488456\" data-score=\"-1\" data-position-on-page=\"1\" data-highest-scored=\"1\" data-question-has-accepted-highest-score=\"1\" itemprop=\"acceptedAnswer\" itemscope itemtype=\"https:\/\/schema.org\/Answer\">\n<div class=\"post-layout\">\n<div class=\"votecell post-layout--left\"><\/div>\n<div class=\"answercell post-layout--right\">\n<div class=\"s-prose js-post-body\" itemprop=\"text\">\n<p>Here I will help you by providing you the template code that you can use and modify according to your needs. I am only going to do for one algorithm then it is your responsibility to do it for others.<\/p>\n<pre class=\"lang-py prettyprint-override\"><code>import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n# read the dataset\ndf = pd.read_csv(\"data.csv\")\n\n# shape of the dataset\ndf.shape\n\n# column names of the dataset\ndf.columns\n\n# descriptive statistics\ndf.describe()\n\n# checking for missing values\ndf.isnull().sum()\n\n# checking the data type of each column\ndf.dtypes\n\n# visualizing the relationship between the features and the target variable\nfor column in df.columns:\n    if column != 'target':\n        plt.scatter(df[column], df['target'])\n        plt.xlabel(column)\n        plt.ylabel('target')\n        plt.show()\n\n# visualizing the distribution of the features\nfor column in df.columns:\n    plt.hist(df[column])\n    plt.xlabel(column)\n    plt.ylabel('count')\n    plt.show()\n    \n# visualizing the correlation between the features\nplt.figure(figsize = (12,10))\ncor = df.corr()\nsns.heatmap(cor, annot=True, cmap=plt.cm.Reds)\nplt.show()\n\n# Data Transformation including removing or imputing missing values, standardization, and normalization\n# imputing missing values\nfrom sklearn.impute import SimpleImputer\n\nimputer = SimpleImputer(missing_values=np.nan, strategy='mean')\nimputer.fit(df)\ndf = imputer.transform(df)\n\n# standardization\nfrom sklearn.preprocessing import StandardScaler\n\nscaler = StandardScaler()\nscaler.fit(df)\ndf = scaler.transform(df)\n\n# normalization\nfrom sklearn.preprocessing import Normalizer\n\nnormalizer = Normalizer()\nnormalizer.fit(df)\ndf = normalizer.transform(df)\n\n# Class balancing\n# checking the number of classes\ndf['target'].value_counts()\n\n# splitting the dataset into feature and target variables\nX = df.drop(['target'], axis=1)\ny = df['target']\n\n# balancing the dataset using the SMOTE technique\nfrom imblearn.over_sampling import SMOTE\n\nsm = SMOTE(random_state=42)\nX_res, y_res = sm.fit_resample(X, y)\n\n# checking the number of classes after balancing\npd.Series(y_res).value_counts()\n\n# Principal Component Analysis\nfrom sklearn.decomposition import PCA\n\npca = PCA(n_components=3)\npca.fit(X_res)\nX_pca = pca.transform(X_res)\n\n# Model training\nfrom sklearn.tree import DecisionTreeClassifier\n\nmodel = DecisionTreeClassifier(random_state=42)\nmodel.fit(X_pca, y_res)\n\n# Model Validation including performance metrics\nfrom sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n\ny_pred = model.predict(X_pca)\n\nprint(\"Accuracy: \", accuracy_score(y_res, y_pred))\nprint(\"Precision: \", precision_score(y_res, y_pred))\nprint(\"Recall: \", recall_score(y_res, y_pred))\nprint(\"F1 Score: \", f1_score(y_res, y_pred))\n\n# Feature importance\nfeature_importances = model.feature_importances_\n\n# plotting the features in descending order of their importance\nindices = np.argsort(feature_importances)[::-1]\n\nplt.figure(figsize=(15,10))\nplt.title(\"Feature Importance\")\nplt.bar(range(X_pca.shape[1]), feature_importances[indices], color=\"r\", align=\"center\")\nplt.xticks(range(X_pca.shape[1]), indices)\nplt.xlim([-1, X_pca.shape[1]])\nplt.show()\n<\/code><\/pre>\n<p>Now in most part the code will going to remain same. Here I suggest you to learn the meaning of words that you find unfamiliar. In addition, also refer to the documentation of the library that I have used. It might make your remaining task easier. Also, learn the concepts after tomorrow as homework is for you. Its fun, give it a try.<\/p>\n<\/p><\/div>\n<div class=\"mt24\"><\/div>\n<\/div>\n<p>            <span class=\"d-none\" itemprop=\"commentCount\">1<\/span> <\/p><\/div>\n<\/div>\n<p>[ad_2]<\/p>\n<p>solved can you guys help me by telling how to do these tasks using python [closed] <\/p>\n","protected":false},"excerpt":{"rendered":"<p>[ad_1] Here I will help you by providing you the template code that you can use and modify according to your needs. I am only going to do for one algorithm then it is your responsibility to do it for others. import pandas as pd import numpy as np import matplotlib.pyplot as plt # read &#8230; <a title=\"[Solved] can you guys help me by telling how to do these tasks using python [closed]\" class=\"read-more\" href=\"https:\/\/jassweb.com\/solved\/solved-can-you-guys-help-me-by-telling-how-to-do-these-tasks-using-python-closed\/\" aria-label=\"More on [Solved] can you guys help me by telling how to do these tasks using python [closed]\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[320],"tags":[586,1173,482],"class_list":["post-28114","post","type-post","status-publish","format-standard","hentry","category-solved","tag-artificial-intelligence","tag-machine-learning","tag-python-3-x"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>[Solved] can you guys help me by telling how to do these tasks using python [closed] - JassWeb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jassweb.com\/solved\/solved-can-you-guys-help-me-by-telling-how-to-do-these-tasks-using-python-closed\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] can you guys help me by telling how to do these tasks using python [closed] - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] Here I will help you by providing you the template code that you can use and modify according to your needs. 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