4 -Machine learning, code for identifying the outliers in jupyter notebook

Here’s an example Python code for identifying outliers in a machine learning dataset using Jupyter Notebook: In this example code, we first load the dataset into a pandas dataframe using the pd.read_csv() function. We then define a function called detect_outliers that takes in a dataset and uses the z-score method to detect outliers. The function first calculates the mean and […]

3- Machine learning, code for identifying the outliers in jupyter notebook

Here’s an example Python code for identifying outliers in a dataset using machine learning in Jupyter Notebook: pythonCopy codeimport pandas as pd import numpy as np from sklearn.ensemble import IsolationForest # load the dataset data = pd.read_csv(“path/to/dataset.csv”) # extract the columns of interest columns_of_interest = [“col1”, “col2”, “col3”] X = data[columns_of_interest].values # create an instance of the Isolation Forest algorithm […]

1-Machine learning, code for identifying the outliers in jupyter notebook

Certainly, here’s an example Python code for identifying outliers in a dataset using machine learning in a Jupyter notebook: pythonCopy codeimport pandas as pd import numpy as np from sklearn.ensemble import IsolationForest # load the dataset into a pandas dataframe data = pd.read_csv(‘dataset.csv’) # specify the column(s) to be used for outlier detection X = data[[‘column1’, ‘column2’]] # create an […]