To successfully complete Assignment 2 on data exploration and preparation using KNIME, follow these step-by-step guidelines to address tasks A3 and B:
1. Load Your Dataset:
2. Exploring the Dataset:
Identify Outliers:
Identify Clusters:
Identify Interesting Attributes and Values:
3. Recoding Attributes:
B1. Binning Techniques for Rainfall:
Equi-width binning:
Rainfall
attribute.Equi-depth binning:
Rainfall
attribute.B2. Normalization of MaxTemp:
Min-max normalization:
MaxTemp
attribute.z-score normalization:
MaxTemp
attribute.B3. Discretising WindSpeed3pm:
Discretization:
WindSpeed3pm
into "Slow Wind," "Medium Wind," "Fast Wind," and "Very Fast Wind."
$WindSpeed3pm$ <= 10 => "Slow Wind"
$WindSpeed3pm$ > 10 AND $WindSpeed3pm$ <= 20 => "Medium Wind"
$WindSpeed3pm$ > 20 AND $WindSpeed3pm$ <= 30 => "Fast Wind"
$WindSpeed3pm$ > 30 => "Very Fast Wind"
B4. Binarising WindDir9am:
Binarization:
WindDir9am
.
if (column("WindDir9am") == "some_value") {
1
} else {
0
}
For each task, ensure you have included:
Save all KNIME workflows and results to include as supporting documentation.
Following these steps will help you systematically explore and preprocess your dataset using KNIME, ensuring you meet the requirements for your assignment. Feel free to reach out if you need further clarification on any step.
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