From the course: Artificial Intelligence Foundations: Machine Learning

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Reviewing learning algorithms for regression

Reviewing learning algorithms for regression

From the course: Artificial Intelligence Foundations: Machine Learning

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Reviewing learning algorithms for regression

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- [Instructor] Do you remember the term regression? If you recall, regression problems are used to predict numeric values like the cost of a home. We'll solve a regression problem using three common regression algorithms, linear regression, RandomForestRegressor, and XGBoost. If you're a homeowner, have you wondered what your home will sell for in the current market? We can train a model to answer the question by taking features of a home to predict what it will sell for. After processing the raw dataset, imputing missing values, adding one-hot encoding of categorical data, removing outliers, and combining highly correlated features, we are left with data in a format that a machine can learn from. In the data, you'll see the median house value, which is the target variable that the machine learns how to predict. The dataset also includes the housing median age, median income, rooms per household, bedrooms per room, population per household, coordinates, and the ocean proximity. We'll…

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