When working on the Python project, if you receive the error message stating, “NameError: name ‘StandardScaler’ is not defined,” it means sci-kit-learn, an open-source library for machine learning, has not been included in the array of tools in use. Let’s simplify what this means b...
Preparation work: Firstly, it is necessary to ensure that Python has been installed and the relevant environment has been configured. 2. Install the Feature engine library: You can install it by running 'pip install feature engine' from the command line. Dependent class libraries: 1. Feature en...
Both normalization and standardization can be achieved using the scikit-learn library. Let’s take a closer look at each in turn. Data Normalization Normalization is a rescaling of the data from the original range so that all values are within the new range of 0 and 1. Normalization requires...
By this, the entire data set scales with a zero mean and unit variance, altogether. Let us now try to implement the concept of Standardization in the upcoming sections. Python sklearn StandardScaler() function Python sklearn library offers us with StandardScaler() function to standardize the data...
257, in decision_function X = check_array(X, accept_sparse=‘csr’) File “D:\Python\...
pythonherokuflaskdotenvmachine-learningneural-networkspotify-apipandaslogistic-regressiontableausvm-classifierscikitlearn-machine-learningspotipynumpy-libraryrandom-forest-classifierjoblibstandardscalerminmaxscalar UpdatedJan 23, 2023 Jupyter Notebook rochitasundar/Stock-clustering-using-ML ...