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What is Bootstrap

Security, Privacy, and Forensics Issues in Big Data
Statistical method for creating samples from a population or to small part of code for starting a computer. Derived expression for the initialization phase of analytic algorithms.
Published in Chapter:
Theoretical Foundations of Deep Resonance Interference Network: Towards Intuitive Learning as a Wave Field Phenomenon
Christophe Thovex (LAFMIA (UMI 3175), France & Mexico)
Copyright: © 2020 |Pages: 23
DOI: 10.4018/978-1-5225-9742-1.ch015
Digital processes for banks, insurances, or public services generate big data. Hidden networks and weak signals from frauds activities are sometimes statistically undetectable in the endogenous data respective to processes. The organic intelligence of human experts is able to reverse-engineer new fraud scenarios without statistically significant characteristics, but machine learning usually needs to be taught about them or fails to this task. Deep resonance interference network is a multidisciplinary attempt in probabilistic machine learning inspired from waves temporal reversal in finite space, introduced for big data analysis and hidden data mining. It proposes a theoretical alternative to artificial neural networks for deep learning. It is presented along with experimental outcomes related to fraudulent processes generating data statistically similar to legal endogenous data. Results show particular findings probably due to the systemic nature of the model, which appears closer to reasoning and intuition processes than to the perception processes mainly simulated in deep learning.
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Can Blockchain Really Help the Poor?: If So, Who Is Trying To?
To self-start a project using founders’ own resources.
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Measuring the Effects of Data Mining on Inference
A resample-the-data strategy that has many applications related to uncertainty quantification.
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Other New Firm Types
A new technology-based enterprise with economic gain intentions basing its resources on economic gains from a commercial activity while endeavoring to perform R&D as the basis for future growth.
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On the Evaluation of Early Warning Models for Financial Crises
A statistical technique consisting in randomly re-sampling with replacement the observed sample, in order to generate artificial samples and finally derive a distribution for the statistics of interest.
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Ensemble of SVM Classifiers for Spam Filtering
Resampling technique based on several random samples drawn with replacement.
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