What are different stages of Data mining

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Hi, 

Kindly tell me about the different stages of Data mining?

Please solve my problem as soon as possible.

Thanks in advance.

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Best Answer by riazbd143
Answered By 25 points N/A #128352

What are different stages of Data mining

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There are three stages of data mining:
 
1. Exploration: At this stage, data are collected and prepared. Transformation and cleansing of the data are also included in this stage. Data has to be analyzed and depending on its size, various tools for analyzing it might be needed. Exploration helps determine the variables of the data.
 
2. Model building and variation: Also known as pattern identification, this stage is about choosing the best model on a basis of their predictive performance. It is then applied and compared with a different data set for the best performance. This stage is complex as it involves allowing easy predictions by choosing the best pattern. 3. Deployment: To estimate the expected outcome or generate predictions, models selected in the previous stage apply to data sets.
 
Answered By 0 points N/A #128354

What are different stages of Data mining

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Exploration: This stage start with preparing data such as data cleaning, transformation, selecting and records. Based on sized of data, different tools to analyze the data may be required. This stage helps to determine different variable of the data to determine their behavior.

ModelBuildingand Validation: In this stage involves choosing the best model based on their predictive performance. This sounds like an easy task but can be difficult. This stage is also called as pattern identification.

Deployment: Until the consistent pattern is found in stage in stage 2, can be applied for the purpose to see whether the desired outcome achieved.

Answered By 0 points N/A #128355

What are different stages of Data mining

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There are certain stages that you must certainly familiar with. Those are exploration, pattern identification and deployment. EXPLORATION means explore and prepare data. You will clean the data and transformed it into another form. PATTERN IDENTIFICATION is somewhat complex.
 
If your looking for a data to find patterns that will allow you to store to earn more profits, you could take two shopping patterns of your customer and apply them to a hypothetical strategy to determine which one performs best.
 
Lastly, DEPLOYMENT, this stage you must found a consistent pattern from pattern identification that is highly predictive.
Answered By 0 points N/A #128356

What are different stages of Data mining

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There are certain stages to data mining that you will want to become familiar with, and these are exploration, pattern identification, and deployment.

1. EXPLORATION:

Exploration is the first stage, and as the name implies, you will want to explore and prepare data. You may need to clean the data you have, or it may need to be transformed into another form.

2. PATTERN IDENTIFICATION:

After you've explored, refined, and defined specific variables, you will next want to move on to stage 2, which is also called pattern identification.

3. DEPLOYMENT:

The third stage is called deployment. You will not want to move to this stage until you have found a consistent pattern from stage 2 that is highly predictive.

Answered By 200 points N/A #128357

What are different stages of Data mining

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There are three stages of the Data Mining Process. The first stage of Data Mining Process is Exploration and has a goal of to find important variables and determine their nature. You might have to clean the data you have so that it could be transformed into another form. Also create some records and have a large number of variables to consider.

You may also need to reduce a range that is easy to deal with based on what kind of problem that you are trying to solve. The wider selection of tools in the order to analyze your data. The second stage is Pattern Identification. You will look for patterns and choose one that will allow you to make the best predictions.

There will be a wide variety of different ways you can find the best predictive patterns. The patterns will allow your store to earn more profits. Last the third stage is Deployment. You will have found a consistent pattern from the second stage.

Many of your customers are consistently buying a specific product on a certain date. Data mining is very popular term for many companies and organizations.

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Best Answer
Answered By 0 points N/A #128359

What are different stages of Data mining

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There are three separate stages of data mining, (1) exploration, (2) model building, and (3) deployment. .

EXPLORATION:

Exploration is the first stage where you can explore and prepare data. You may need to clean the data of it. It may need to be transformed into another form. You may also need to create records. The goal of the exploration stage is to find important variables and determine their nature. 

MODEL BUILDING:

This stage involves choosing the best model based on there predictive performance. This sounds like an easy task but can be difficult. Several different methods may be used to determine which model is best for you.

DEPLOYMENT:

The third stage is called deployment. You will not want to move to this stage until you have found a consistent pattern from stage 2 that is highly predictive. 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.

Answered By 0 points N/A #128361

What are different stages of Data mining

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The data mining and cluster relationships.

Most marketers understand the value of collecting Cluster data, but also realize the challenges of leveraging this knowledge to create intelligent, proactive pathways back to the customer. Data mining – technologies and techniques for recognizing and tracking patterns within data –

Helps, business sift though layers of seemingly unrelated data for meaningful relationships, where they can anticipate, rather than simply react to, customer needs.

I hope you can get idea.

Thank you and more Power.

Regards;

henry

Answered By 0 points N/A #128362

What are different stages of Data mining

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Here is the answer to your question.
 
1. Exploration: Data is collected and prepared in this stage. Data is also transformed and cleaned in this stage when necessary. Exploration helps determining the variables of the data to determine their behavior.
 
2. Model building and validation: The principal objective of this stage is to search for different patterns and determine the one that allows making the best predictions. There is a wide range of ways to achieve this target, which is applying different models to the same set of data and comparing them for the best performance. These techniques are usually known as the core of predictive data mining, which includes bagging, boosting, stacking and meta-learning.
 
3. Deployment: Deployment is the final stage of data mining. The model selected after comparing for the best performance is applied to a new set of data for generating predictions.
 

 

Answered By 0 points N/A #128363

What are different stages of Data mining

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To begin with Data mining can be described as a logical process that is used to search through bulk amounts of information in order to find important data. The aim of this technique is to find patterns that were previously unknown. Behavior patterns gotten from data mining can be used to solve a number of problems.

Once have gotten a hand of a data mining behavior pattern, you will be able to make strategic decisions that can allow you to achieve certain goals. In other to achieve data mining you will have to be familiar with the 3 stages of data mining which are: exploration, pattern identification, and deployment. Read for detailed explanation of stages data mining.

Stages of Data Mining:

Exploration Stage:

This is the first stage and as the name implies, you will want to explore and prepare data. Here the data gotten may need to be cleaned or transformed into another form. Also in addition to this you may need to create records. If a large number of variables where gathered during your exploration you may need to reduce them to a range that is easy to deal with.

You may need to use a wider selection of tools in order to analyze the data. Example of tools you could use are graphs and statistics. The exploration stage is all about finding the important variables and determining their nature.

Pattern Identification Stage:

After exploration is the second stage which is known as pattern identification. At this stage you will look for look for patterns and choose the ones that will allow you to make the best predictions. This stage of data mining can be somewhat complex. There are a variety of ways you can use to find the best predictive patterns.

One of the best ways is to apply different patterns to a given situation and determine which one performs at the highest level. For example, if you are looking at data to find patterns that will allow your store to increase your profits, you could take two shopping patterns of your clients and apply them to a hypothetical strategy to determine which one would result to the best.

Deployment Stage:

The third of the data mining stages which is the last stage is called deployment. This stage comes after you must have found a consistent pattern that is highly predictive from stage 2. For example, if you find more customers purchasing a specific product on a certain date, you will be able to predict their future behavior pattern. Now that you've done this, you can take the pattern and apply it in order to see if you can achieve your desired outcome.

I hope my explanation of the stages was helpful to you.

Answered By 0 points N/A #128364

What are different stages of Data mining

qa-featured

There are three stages of the Data Mining Process. The first stage of Data Mining Process is Exploration and has a goal of to find important variables and determine their nature. You may need to clean the data you have, or it may need to be transformed into another form.

After explored, refined, and defined specific variables, next stage is called pattern identification.

Until the consistent pattern is found in earlier stage deployment can be applied for the purpose to see whether the desired outcome achieved.

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