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Decoding student cognitive abilities: a comparative study of explainable AI algorithms in educational data mining

Flipboard

This study employs data-driven artificial intelligence (AI) models supported by explainability algorithms and PSM causal inference to investigate the factors influencing students’ cognitive abilities, and it delved into the differences that arise when using various explainability AI algorithms to analyze educational data mining models.

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Data mining

Dataconomy

Data mining is a fascinating field that blends statistical techniques, machine learning, and database systems to reveal insights hidden within vast amounts of data. Businesses across various sectors are leveraging data mining to gain a competitive edge, improve decision-making, and optimize operations.

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Understanding Associative Classification in Data Mining

Pickl AI

Summary: Associative classification in data mining combines association rule mining with classification for improved predictive accuracy. Despite computational challenges, its interpretability and efficiency make it a valuable technique in data-driven industries. Lets explore each in detail.

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Muvera: Making multi-vector retrieval as fast as single-vector search

Hacker News

The embeddings are generally compared via the inner-product similarity , enabling efficient retrieval through optimized maximum inner product search (MIPS) algorithms. We have provided an open-source implementation of our FDE construction algorithm on GitHub.

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Android Earthquake Alerts: A global system for early warning

Hacker News

We’re excited to continue to show how the devices in so many of our pockets can be used to create a more informed and safer world.

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Data preprocessing

Dataconomy

Data preprocessing is a crucial step in the data mining process, serving as a foundation for effective analysis and decision-making. It ensures that the raw data used in various applications is accurate, complete, and relevant, enhancing the overall quality of the insights derived from the data.

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Noisy data

Dataconomy

Understanding the complexities of noisy data is essential for improving data quality and enhancing the outcomes of predictive algorithms. What is noisy data? Noisy data pertains to irrelevant, erroneous, or misleading information that can hinder data clarity and integrity.