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| Label | Prediction |
|---|---|
| 2 | This value indicates that the situation is benign. |
| 4 | This value indicates that the situation is malignmalignant. |
The following steps demonstrate how the Machine Learner can use this dataset to make a prediction.
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- Log into the ML UI if you are not already logged in.
- Click the You have X projects link as shown below.
- Click on the Breast_Cancer_data_analytics_project project to expand it.
- Enter breast_cancer_analysis_1 as the analysis name and click CREATE ANALYSIS. The following page will appear displaying the summary statistics.
- Click Next without making any changes to the summary statistics.
The Explore view will open. You will notice that Parallel Sets and Trellis Chart visualisations are enabled, and Scatter Plot and Cluster Diagram visualisations are disabled. This is determined by the feature types of the dataset. Select and clear the checkboxes for categorical features as follows.
Click Next. The Algorithms view will be displayed. Enter values as shown below.
Parameter Value Algorithm name LOGISTIC REGRESSION L_BFGS Response variable Class Train data fraction 0.7 - Click Next. The Parameters view will appear. Enter L2 as the reg type.
- Click Next. The Model view will appear. Select Breast_Cancer_Dataset-1.0.0 as the dataset version.
- Click RUN to perform train the analysismodel.
The analysis will be created and displayed for the project as shown below.
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