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types of data reduction

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12y ago
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6mo ago

Data reduction in data mining refers to the process of reducing the volume of data under consideration. This can involve techniques such as feature selection, dimensionality reduction, or sampling to simplify the dataset and make it more manageable for analysis. By reducing the data, analysts can focus on the most relevant information and improve the efficiency of their data mining process.

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Q: What is data reduction in terms of data mining?
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What are the short terms of data mining?

Short terms related to data mining include: ML (Machine Learning): The use of algorithms to learn from and make predictions on data. EDA (Exploratory Data Analysis): Analyzing and visualizing data to understand patterns and relationships. Clustering: Grouping similar data points together based on certain criteria. Regression: Predicting a continuous outcome based on input variables.


What are the seminar topics related to data mining?

Some seminar topics related to data mining could include: Introduction to data mining techniques and algorithms Applications of data mining in business intelligence Big data analytics and data mining Ethical considerations in data mining and privacy protection.


How Data warehousing and Data Mining is useful in terms of MIS?

Data warehousing and data mining contribute to Management Information Systems (MIS) by providing a centralized location for storing and accessing data, enabling users to run complex queries and generate reports for strategic decision-making. Data mining techniques help uncover patterns and trends in the data, allowing organizations to gain valuable insights and make informed decisions based on the information retrieved from the data warehouse. Ultimately, these tools enhance the effectiveness of MIS by facilitating more efficient data analysis and interpretation.


What is directed data mining and undirected data mining in database?

Directed data mining involves using predefined goals or objectives to guide the analysis and modeling of data. In contrast, undirected data mining aims to discover patterns or relationships in data without specifying a particular outcome in advance. Directed data mining is typically used for tasks such as classification and regression, while undirected data mining techniques include clustering and anomaly detection.


Different types of data mining?

Some different types of data mining include clustering, classification, regression, association rule mining, and anomaly detection. Clustering involves grouping similar data points together, while classification involves categorizing data into predefined classes. Regression predicts a continuous value based on input variables, and association rule mining uncovers patterns in data sets. Anomaly detection identifies unusual or outlier data points.

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Characteristics of data mining?

CHARECTERISTICS OF DATA MINING CHARECTERISTICS OF DATA MINING


Distinguish between Data mining and text mining?

mining the data is called data mining. Mining the text is called text mining


What are the short terms of data mining?

Short terms related to data mining include: ML (Machine Learning): The use of algorithms to learn from and make predictions on data. EDA (Exploratory Data Analysis): Analyzing and visualizing data to understand patterns and relationships. Clustering: Grouping similar data points together based on certain criteria. Regression: Predicting a continuous outcome based on input variables.


What are the seminar topics related to data mining?

Some seminar topics related to data mining could include: Introduction to data mining techniques and algorithms Applications of data mining in business intelligence Big data analytics and data mining Ethical considerations in data mining and privacy protection.


How Data warehousing and Data Mining is useful in terms of MIS?

Data warehousing and data mining contribute to Management Information Systems (MIS) by providing a centralized location for storing and accessing data, enabling users to run complex queries and generate reports for strategic decision-making. Data mining techniques help uncover patterns and trends in the data, allowing organizations to gain valuable insights and make informed decisions based on the information retrieved from the data warehouse. Ultimately, these tools enhance the effectiveness of MIS by facilitating more efficient data analysis and interpretation.


What services do the data mining company provide?

Data Mining companies provide such services as mining for data and mining for data two electric bugaloo. They will often offer to resort to underhanded tactics to mine said data.


What are the key relationships between data warehouse and data mining?

Data warehouse is the database on which we apply data mining.


How do you put data mining in a sentence?

Data mining can uncover interesting patterns. Some cookies will upload solely for the purpose of data mining.


What is data mining in data processing?

Simply, Data mining is the process of analyzing data from several sources and converting it into useful data.


Where can one learn online what is data mining?

One can learn about data mining by visiting the data mining wikipedia page, which has a very comprehensive article about the topic, starting with the etymology and mostly talking about the various uses of data mining.


Which of the following is the computer-assisted process of sifting through and analyzing vast amounts of data to extract meaning and discover new knowledge?

Data mining


What is the difference between OLAP and data mining?

difference between Data Mining and OLAP