| Cross-Validation |
A technique used to assess the performance of a predictive model by splitting the data into multiple subsets. |
| Data Cleaning |
The process of removing errors and inconsistencies from the collected data before further analysis. |
| Data Collection |
The first step in the predictive modelling process, involving gathering relevant data from various sources. |
| Data Preparation |
The process of cleaning, transforming, and organizing data before building a predictive model. |
| Decision Tree |
A flowchart-like structure in which each internal node represents a test on an attribute, each branch represents the outcome of the test, and each leaf node represents a class label. |
| Deployment |
Where the model is put into practical use for making predictions. |
| Ensemble Learning |
A machine learning technique that combines multiple models to improve the overall performance and accuracy of the prediction. |
| Feature Selection |
The process of choosing the most relevant input variables to be used in the predictive model. |
| Gradient Boosting |
An ensemble learning method that builds a model in a stage-wise manner, with each new model addressing the errors of the previous models. |
| K-Nearest Neighbors |
A non-parametric method used for classification and regression that classifies a data point based on the majority class of its k nearest neighbors. |
| Logistic Regression |
A statistical method used to model binary outcomes by estimating the probability that a given outcome is present. |
| Model Evaluation |
The process of assessing the performance of the predictive model using validation data sets. |
| Model Training |
The stage where the predictive model is developed using the selected features and training data. |
| Model Tuning |
The step where adjustments are made to the model to improve its predictive accuracy and performance. |
| Monitoring |
The ongoing process of evaluating the model's performance and making updates as needed to maintain accuracy. |
| Neural Network |
A network of interconnected nodes, similar to neurons in the brain, that processes information by mimicking the way the human brain functions. |
| Predictive Modelling Process |
The process of using data and statistical algorithms to create models that predict future outcomes or trends. |
| Random Forest |
An ensemble learning method that constructs a multitude of decision trees at training time and outputs the mode of the classes as the prediction. |
| Regression Analysis |
A statistical method used to examine the relationship between one dependent variable and one or more independent variables. |
| Support Vector Machine |
A supervised machine learning algorithm that classifies data into different classes by finding the hyperplane that best separates the data points. |
| Time Series Forecasting |
A technique used to forecast future values based on past data points in time order. |
