Tasks for Group 1 in KNIME Data Science Learnathon
- Access data
- Preprocess data by filtering rows, filtering columns, converting column types, and handling missing values
- Join data from two different sources
- Generate new features by binning and by a rule
- Remove outliers
- Normalize data
- Partition data into a training and a test set
- Write data into a file
External resources
- Original Airline Dataset
- Outlier Detection in Medical Claims
- KNIME Analytics: a Review
- KNIME E-Learning Course - Data Manipulation
- Partitioning
- Normalization
- Four Techniques for Outlier Detection
- Four Techniques for Outlier Detection
- 7 Techniques for Data Dimensionality Reduction
- Dimensionality Reduction and Feature Selection
- Missing Values
- Will They Blend? The Blog Post Collection
- Analytics - Model Selection to Predict Flight Departure Delays
Used extensions & nodes
All required extensions are part of the default installation of KNIME Analytics Platform version 4.4.2
No known nodes available
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