1					13
	11
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			12
4
							14
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9
	10

Across

1. A supervised machine learning algorithm that classifies data into different classes by finding the hyperplane that best separates the data points.

2. The process of cleaning, transforming, and organizing data before building a predictive model.

3. Enabling computers to learn and make decisions from data without being explicitly programmed.

4. The automated recognition of patterns and regularities in data.

5. A statistical method used to model binary outcomes by estimating the probability that a given outcome is present.

6. A non-parametric method used for classification and regression that classifies a data point based on the majority class of its k nearest neighbors.

7. A network of interconnected nodes, similar to neurons in the brain, that processes information by mimicking the way the human brain functions.

8. Selecting a subset of relevant features from the original dataset to improve the performance of a machine learning model.

9. A statistical method used to examine the relationship between one dependent variable and one or more independent variables.

10. An ensemble learning method that builds a model in a stage-wise manner, with each new model addressing the errors of the previous models.

Down

11. A technique used to assess the performance of a predictive model by splitting the data into multiple subsets.

12. The first step in the predictive modelling process, involving gathering relevant data from various sources.

13. An ensemble learning method that constructs a multitude of decision trees at training time and outputs the mode of the classes as the prediction.

14. The process of assessing the performance of the predictive model using validation data sets.

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