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├── main.py # Main pipeline orchestrator ├── FeatureExtractor/ # Feature extractor package │ ├── __init__.py # Package exports │ ├── base.py # Abstract base class & enum │ ├── count_vectorizer.py # ...

3.Import the Logistic Regression model from sklearn. 4.Train the model using the training dataset. 5.Use the trained model to predict placement for new student data. from sklearn.preprocessing import ...

In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model. This can be a ...

Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...

Abstract: We present a versatile GPU-based parallel version of Logistic Regression (LR), aiming to address the increasing demand for faster algorithms in binary classification due to large data sets.

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...

1 Department of Business Information System, Central Michigan University, Mount Pleasant, MI, USA. 2 Department of MPH, Central Michigan University, Mount Pleasant, MI, USA. 3 Department of ...