Predictive Analysis

Explore Our Recent Predictive Analysis Technologies

Data Preparation

The first step in predictive analysis is data preparation, which involves collecting relevant data, cleaning and preprocessing it, handling missing values or outliers, and transforming it into a suitable format for analysis.

Feature Selection

Feature selection is the process of identifying the most relevant and informative variables or features that will be used in the predictive model. It helps reduce the dimensionality of the data and focuses on the features that have the most impact on the target variable.

Model Training and Evaluation

In predictive analysis, models are trained on historical data and evaluated using appropriate metrics to assess their performance. Techniques such as cross-validation, holdout testing, and performance metrics like accuracy, precision, recall, and F1 score are used to measure the model's accuracy and generalizability..

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