Visual Programming with Orange Tool.

Data Sampler

Selects a subset of data instances from an input dataset.

The Data Sampler widget implements several data sampling methods. It outputs a sampled and a complementary dataset (with instances from the input set that are not included in the sampled dataset). The output is processed after the input dataset is provided and Sample Data is pressed.

How to Split our data in training data and testing data in Orange?

Creating Classification Model to find Accuracy:

What is the effect of splitting data on classification result/ classification model?

When Splitting the Data in 50% training and 50% testing dataset, we get

Train and Test Accuracy.

When Splitting the Data in 70% training and 30% testing dataset, we get

Train and Test Accuracy.

When Splitting the Data in 90% training and 10% testing dataset, we get

Train and Test Accuracy.

We can see that by increasing the training data the Accuracy also gets increase.

How to efficiently use cross-validation in Orange? What is the effect of it on model output/accuracy?

For Number of Folds = 5,

For Number of Folds = 10,

For Number of Folds = 3,

We can see the highest ACCURACY in for Number of Folds = 5.

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