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San Francisco Crime Classification - Modelling

import Packages

import warnings
warnings.filterwarnings('ignore')

import pickle
import os
import pandas as pd
import numpy as np
import itertools
import matplotlib.pyplot as plt
import seaborn as sns

from datetime import datetime
from tabulate import tabulate

from sklearn.metrics import confusion_matrix
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.preprocessing import StandardScaler
from sklearn.metrics import log_loss
from sklearn import metrics
from sklearn.model_selection import GridSearchCV
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.dummy import DummyClassifier
from sklearn.calibration import CalibratedClassifierCV

from xgboost import XGBClassifier

Data Reading

project_path = '/content/drive/MyDrive/AAIC/SCS-1/sf_crime_classification/'