Machine Learning
The Machine Learning category includes modeling tools for both classification and regression. The Machine Learning tools are based on ayx-learn, which is built on Scikit-learn.
Code-free tools
The Assisted Modeling tool simplifies the model-building process. With Assisted Modeling, you're guided through the process of building and evaluating several predictive models and selecting the one that best suits your business use case. Assisted Modeling helps you identify a target, set data types, select features, select the most relevant algorithms, and build your models.
Assisted Modeling Tool Predict Tool
The Predict tool makes predictions on new data with your model. After you've trained a model or models, you can score your models using the Predict tool. To generate predictions, input a model built using the Machine Learning tools and representative test data.
Fit Tool Machine Learning Tool
Transformation tools:
Missing Value Imputation Transformer
Assisted Modeling Tool Classification Tool
The Classification category includes the following tools:
- Decision Tree Classifier: The Decision Tree tool predicts a target variable using one or more variables that are expected to have an influence on the target variable.
- Random Forest Classifier: The Forest Model tool predicts a target variable using one or more variables that are expected to have an influence on the target variable.
- Logistic Regression Classifier: The Logistic Regression tool relates a binary (e.g., yes/no) variable of interest (a target variable) to one or more variables that are expected to have an influence on the target variable.
Machine Learning Tools
Definitions for Machine Learning Tools
Steps in Assisted Modeling
Select Target and Machine-Learning Method
Other Machine Learning Tools
One Hot Encoding Machine Learning Tool
Fit Tool Machine Learning Tool