- Learn how to build basic Machine Learning models using KNIME
- Build Top 5 Use Cases in Machine Learning
- Classification
- Regression
- Clustering
- Forecasting
- Text Classification
Classification models are a subset of supervised machine learning . A classification model reads some input and generates an output that classifies the input into some category. For example, a model might read an email and classify it as either spam or not โ binary classification.
Regression is a technique for investigating the relationship between independent variables or features and a dependent variable or outcome. It's used as a method for predictive modelling in machine learning, in which an algorithm is used to predict continuous outcomes.
- Missing Values Treatment
- Numerical - Mean, Median, Mode
- Categorical - Most Frequent, Constant
- Outlier Treatment
- Numerical - Quartile Method
- Transformation
- Numerical - Standard Scaler
- Categorical - Not Required in KNIME
- Ensure Categories are less
- Train Test Split
- 80% Train, 20% Test/Validation