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MOANOFS: Multi-Objective Automated Negotiation based Online Feature Selection System for Big Data Classification

arXiv.org Artificial Intelligence

Abstract-- Feature Selection (FS) plays an important role in learning and classification tasks. The object of FS is to select the relevant and non-redundant features. Considering the huge amount number of features in real-world applications, FS methods using batch learning technique can't resolve big data problem especially when data arrive sequentially. In this paper, we propose an online feature selection system which resolves this problem. More specifically, we treat the problem of online supervised feature selection for binary classification as a decision-making problem. A philosophical vision to this problem leads to a hybridization between two important domains: feature selection using online learning technique (OFS) and automated negotiation (AN). The proposed OFS system called MOANOFS (Multi-Objective Automated Negotiation based Online Feature Selection) uses two levels of decision. In the first level, from n learners (or OFS methods), we decide which are the k trustful ones (with high confidence or trust value). These elected k learners will participate in the second level. In this level, we integrate our proposed Multilateral Automated Negotiation based OFS (MANOFS) method to decide finally which is the best solution or which are relevant features. We show that MOANOFS system is applicable to different domains successfully and achieves high accuracy with several real-world applications. Index Terms-- Feature selection, online learning, multi-objective automated negotiation, trust, classification, big data. URING the last three decades, Feature Selection (FS) has been extensively studied in Data Mining [1], [2], Pattern Classification [3], [4] and Machine Learning [5], [6]. FS is defined as the process of selecting a subset of relevant features and removing the redundant ones from a dataset for building effective prediction models. In recent years, an enormous increase in data (news, medical imaging) has been observed which allows an increase in redundant information. Even worse, the redundancy of irrelevant data has a negative impact on the performance of classification methods associated. With the rapid development of the Internet, current tremendous amounts of data up to millions or billions, can be collected for training machine learning models.


Data Science Nigeria to host AI Summit and Bootcamp

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The summit will focus on understanding the financially excluded segment, use of alternative data (geospatial, social media, mobile footprint, psychographics) in developing credit risk scoring algorithm, and building simpler AI-enabled financial delivery interfaces. The Summit is scheduled to hold on Wednesday, 10 October 2018 at the Oriental Hotel, Victoria Island, Lagos and with the theme, "New Algorithms for the Financially Excluded Segment". This is a broad based stakeholder session focused on understanding emerging trends and advanced data analytics use cases applied to issues of financial inclusion. The one-day Summit will be followed by a five-day residential, all-expenses-paid Artificial Intelligence Bootcamp and Hackathon on emerging trends in machine learning and deep learning between 10 and 14 October 2018. The intent of the bootcamp and hackathon is to build world-class capacity in advanced data analytics, upskill financial inclusion data analysts and researchers in emerging best practices, and to support the development of contextually relevant algorithm and tech innovation.


Machine learning plasma-surface interface for coupling sputtering and gas-phase transport simulations

arXiv.org Artificial Intelligence

Thin film processing by means of sputter deposition inherently depends on the interaction of energetic particles with a target surface and the subsequent particle transport. The length and time scales of the underlying physical phenomena span orders of magnitudes. A theoretical description which bridges all time and length scales is not practically possible. Advantage can be taken particularly from the well-separated time scales of the fundamental surface and plasma processes. Initially, surface properties may be calculated from a surface model and stored for a number of representative cases. Subsequently, the surface data may be provided to gas-phase transport simulations via appropriate model interfaces (e.g., analytic expressions or look-up tables) and utilized to define insertion boundary conditions. During run-time evaluation, however, the maintained surface data may prove to be not sufficient. In this case, missing data may be obtained by interpolation (common), extrapolation (inaccurate), or be supplied on-demand by the surface model (computationally inefficient). In this work, a potential alternative is established based on machine learning techniques using artificial neural networks. As a proof of concept, a multilayer perceptron network is trained and verified with sputtered particle distributions obtained from transport of ions in matter based simulations for Ar projectiles bombarding a Ti-Al composite. It is demonstrated that the trained network is able to predict the sputtered particle distributions for unknown, arbitrarily shaped incident ion energy distributions. It is consequently argued that the trained network may be readily used as a machine learning based model interface (e.g., by quasi-continuously sampling the desired sputtered particle distributions from the network), which is sufficiently accurate also in scenarios which have not been previously trained.


These Delivery Drones Are Impacting World Healthcare

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One of the most important issues we face today is global accessibility to healthcare. The WHO recently revealed that at least half of the world's population isn't able to access essential healthcare services. With large numbers of others being drawn into poverty by healthcare bills. According to the report, as covered by Reuters, there are 800 million people across the world that spend at least 10% of their household income on healthcare. A staggering 100million of those left with less than $1.90 a day to survive on.


Explore Data Science Academy, Alphacode seeks aspiring SA fintech entrepreneurs – Ventureburn

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Do you have an idea that could make you South Africa's most successful fintech entrepreneur? Are you looking to acquire the skills to launch a data-driven fintech business? A new one-year data science and business skills programme aims to assist aspirant SA fintech entrepreneurs. In an announcement today, the Explore Data Science Academy (Edsa) and Rand Merchant Investments' (RMI) fintech division, AlphaCode, said their Explore 10X programme would assist 20 aspiring SA future fintech entrepreneurs. Successful candidates will go through an intensive six-month data science-training programme, where they will learn how to design a fast-growing business along with the core digital skills needed to build a fintech organisation.


CTICC hosts AI robot Miss Pepper

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The Cape Town International Convention Centre hosted Miss Pepper, a humanoid robot capable of detecting human emotions during the recent BIOMIN World Nutrition Forum 2018. Developed by SoftBank Robotics, "Miss Pepper" who is capable of interacting with humans and can adapt her interaction according to a human's emotions, was unveiled during the three-day international conference. According to SoftBank Robotics, the Pepper robot is the "first humanoid robot capable of recognising the principal human emotions and adapting his behaviour to the mood of his interlocutor". Herbert Kneissl, chief marketing officer at Erber AG, the parent company of Biomin, said robotics, artificial intelligence and big data will become an everyday topic in the livestock industry. "She (Miss Pepper) is able to perceive emotions, and what is a conference like the Biomin World Nutrition Forum without emotions? The digital experts of Biomin additionally trained her to be the little star on the stage - to welcome the audience, break the tensions, but in first line to demonstrate that the future of using humanoid robots has started now. "By using Miss Pepper we have the intention to create the image overflow from technological developments of other industries to biotechnology and animal nutrition, an overflow that develops already towards a merger, when we see the modern technologies like Farm 4.0, one of the big topics of this conference," said Kneissl. Miss Pepper is capable of recognising faces, speech, and can hear; she can also identify when someone is experiencing joy, sadness, is surprised and filled with anger. Over and above recognising these emotions, Miss Pepper can also detect tone of voice, smiles, and frowns. Facilitating emerging technologies "At the CTICC, we are committed to facilitating the introduction of emerging technologies such as Miss Pepper to delegates and visitors.


CTICC hosts AI robot Miss Pepper

#artificialintelligence

The Cape Town International Convention Centre hosted Miss Pepper, a humanoid robot capable of detecting human emotions during the recent BIOMIN World Nutrition Forum 2018. Developed by SoftBank Robotics, "Miss Pepper" who is capable of interacting with humans and can adapt her interaction according to a human's emotions, was unveiled during the three-day international conference. According to SoftBank Robotics, the Pepper robot is the "first humanoid robot capable of recognising the principal human emotions and adapting his behaviour to the mood of his interlocutor". Herbert Kneissl, chief marketing officer at Erber AG, the parent company of Biomin, said robotics, artificial intelligence and big data will become an everyday topic in the livestock industry. "She (Miss Pepper) is able to perceive emotions, and what is a conference like the Biomin World Nutrition Forum without emotions? The digital experts of Biomin additionally trained her to be the little star on the stage - to welcome the audience, break the tensions, but in first line to demonstrate that the future of using humanoid robots has started now. "By using Miss Pepper we have the intention to create the image overflow from technological developments of other industries to biotechnology and animal nutrition, an overflow that develops already towards a merger, when we see the modern technologies like Farm 4.0, one of the big topics of this conference," said Kneissl. Miss Pepper is capable of recognising faces, speech, and can hear; she can also identify when someone is experiencing joy, sadness, is surprised and filled with anger. Over and above recognising these emotions, Miss Pepper can also detect tone of voice, smiles, and frowns. Facilitating emerging technologies "At the CTICC, we are committed to facilitating the introduction of emerging technologies such as Miss Pepper to delegates and visitors.


The Most Important Skills for the 4th Industrial Revolution? Try Ethics and Philosophy. - EdSurge News

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For those keeping count, the world is now entering the Fourth Industrial Revolution. That's the term coined by Klaus Schwab, founder and executive chairman of the World Economic Forum, to describe a time when new technologies blur the physical, digital and biological boundaries of our lives. Every generation confronts the challenges of preparing its kids for an uncertain future. Now, for a world that will be shaped by technologies like artificial intelligence, 3D printing and bioengineering, how should society prepare its current students (and tomorrow's workforce)? The popular response, among some education pundits, policymakers and professionals, has been to increase access to STEM and computer science skills.


How Would Your Job Look Like in the Future? Three Bold Predictions

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A new wave of technologies is changing every aspect of human life–from online shopping and scheduling a ride with Uber to completing wells and managing reservoirs. The stuff of science fiction is becoming science fact. The HR Discussion team, via this article, aims to inform young professionals (YPs) about three trends that will change the way we will work in the future. These three trends are introduced in the form of three key questions for YPs. Everything– and everyone–will be measured, recorded, analyzed, and rated.


Activities / Events Machine Intelligence Institute of Africa

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The SA Innovation Summit as an annual flagship event on the South African Innovation Calendar, is a platform for nurturing, developing and showcasing African innovation, as well as facilitating innovation thought-leadership. Created to support and promote innovation and facilitate collaboration within its own eco-system, the initiative brings together corporates, thought leaders, inventors, entrepreneurs, academia and policy makers to amplify South Africa's renowned competitive edge and to inspire sustained economic growth across the continent of Africa. The outcomes achieved by the Summit, is a powerful platform to bring together thought leaders and accelerate innovation in South Africa, and into the African continent as whole. MIIA ill also be represented at the South African Innovation Summit and invitethe MIIA community to also join the 48-hour hackathon being held in Cape Town Stadium from 5 - 7 September 2017.