What are different stages of “Data mining”?Exploration:This stage involves preparation and collection of data. it also involves data cleaning, transformation. Based on size of data, different tools to analyze the data may be required. This stage helps to determine different variables of the data to determine their behavior.
Model building and validation:This stage involves choosing the best model based on their predictive performance. The model is then applied on the different data sets and compared for best performance. This stage is also called as pattern identification. This stage is a little complex because it involves choosing the best pattern to allow easy predictions.
Deployment:Based on model selected in previous stage, it is applied to the data sets. This is to generate predictions or estimates of the expected outcome.
What are different stages of “Data mining”?A stage of data mining is a logical process for searching large amount information for finding important data.
Stage 1: Exploration is the first stage, and as the name implies, you will want to explore and prepare data. The goal of the exploration stage is to find important variables and determine their nature.
Stage 2: Also called pattern identification. Searching for patterns and choosing the one which allows making best prediction, is the primary action in this stage.
Stage 3: Deployment stage. Until consistent pattern is found in stage 2, which is highly predictive, this stage can not be reached. The pattern found in stage 2, can be applied for the purpose to see whether the desired outcome is achieved.