Question

The process of determining the causes that play a role in House Price increase in a particular area to model a House Price predictor is called ___________. None of the options Feature engineering Data pre-processing Data cleaning

Answer 1

Answer:

Feature Engineering(100% sure)

Explanation:

Answer 2

Answer:

The correct answer is Feature engineering.

Explanation:

Feature engineering is the process of selecting, manipulating, and transforming raw data into features that can be used in supervised learning. For machine learning to perform well on new tasks, better features may need to be designed and trained. As you may know, a "feature" is any measurable input that can be used in a predictive model - it could be the color of an object or the sound of someone's voice. Feature engineering, simply put, is the act of converting raw observations into desired features using statistical or machine learning approaches.

What is Feature Engineering

Feature Engineering is a machine learning technique that uses data to create new variables that are not in the training set. It can create new features for both supervised and unsupervised learning to simplify and accelerate data transformations while increasing model accuracy. Regardless of data or architecture, a terrible feature will have a direct impact on your model.

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