INSTRUCTIONS · Use of the following CLASSIFICATION Machine Learning Models · Decision Trees · Random Forest · Gradient Boosting Trees · First, given dataset “spx_tail”, the “tail events” as defined...

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"import pandas as pd\n",
"from sklearn.model_selection import train_test_split, cross_val_score, TimeSeriesSplit\n",
"from sklearn.tree import DecisionTreeClassifier\n",
"from sklearn.metrics import accuracy_score, classification_report\n",
"from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier, VotingClassifier\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from sklearn.linear_model import LogisticRegression\n",
"from sklearn.naive_bayes import GaussianNB\n",
"from sklearn.neighbors import KNeighborsClassifier"
]
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"source": [
"#Reading CSV file\n",
"df = pd.read_csv('spx_tail.csv')"
]
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"source": [
"#Shape of the data\n",
"df.shape"
]
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