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Genetic Algorithms Tutorial 06 - data mining + JAVA 8 + logical operators
 
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Website + download source code @ http://www.zaneacademy.com
Views: 1724 zaneacademy
Naive Bayes w/ JAVA - Tutorial 01
 
16:12
Website + download source code @ http://www.zaneacademy.com
Views: 3112 zaneacademy
Genetic Algorithms Tutorial 04 - Class Scheduling JAVA Application
 
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Website + download source code @ http://www.zaneacademy.com
Views: 15980 zaneacademy
13. Learning: Genetic Algorithms
 
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MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston This lecture explores genetic algorithms at a conceptual level. We consider three approaches to how a population evolves towards desirable traits, ending with ranks of both fitness and diversity. We briefly discuss how this space is rich with solutions. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 308205 MIT OpenCourseWare
Genetic Programming in Java with TinyGP (Part 6 - Data Mining)
 
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A continuing series on Riccardo Poli's TinyGP Java program. In this installment, we make a minor modification by refactoring TinyGP with three logic operators in order to allow the program to do some basic data mining of relationships between input values to a target value. A very obvious toy scenario is first introduced, and then a more involved scenario is built, a formula derived, and an analysis done by with a simple spreadsheet.
Views: 422 Brint Montgomery
Let’s Write a Decision Tree Classifier from Scratch - Machine Learning Recipes #8
 
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Hey everyone! Glad to be back! Decision Tree classifiers are intuitive, interpretable, and one of my favorite supervised learning algorithms. In this episode, I’ll walk you through writing a Decision Tree classifier from scratch, in pure Python. I’ll introduce concepts including Decision Tree Learning, Gini Impurity, and Information Gain. Then, we’ll code it all up. Understanding how to accomplish this was helpful to me when I studied Machine Learning for the first time, and I hope it will prove useful to you as well. You can find the code from this video here: https://goo.gl/UdZoNr https://goo.gl/ZpWYzt Books! Hands-On Machine Learning with Scikit-Learn and TensorFlow https://goo.gl/kM0anQ Follow Josh on Twitter: https://twitter.com/random_forests Check out more Machine Learning Recipes here: https://goo.gl/KewA03 Subscribe to the Google Developers channel: http://goo.gl/mQyv5L
Views: 127830 Google Developers
Cancer Identification Data Mining Java Project
 
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Cancer Identification System Data Mining Java Project Download Project Code, Report and PPT :+91 7702177291, +91 9052016340 Email : [email protected] Website : www.1000projects.org
Views: 565 1000 Projects
Association Rule Mining Project in Java PPT
 
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Download Association Rule Mining Project in Java PPT Source code in java, project report, documentation, ppt for free download. http://freeprojectscode.com/java-projects/association-rule-mining/1237/ http://1000projects.org/efficient-association-rule-mining-algorithm-distribute-project-java.html
Views: 983 kasarla shashank
Java Implementation of the Perceptron Algorithm
 
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My web page: www.imperial.ac.uk/people/n.sadawi
Views: 26696 Noureddin Sadawi
How to add algorithm to weka
 
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this video explains how to add and modify the weka source code
Views: 17907 saed muqasqas
Using Genetic Algorithms for Network Intrusion Detection and Integration into nProbe
 
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From Ignite at OSCON 2010, a 5 minute presentation by Bill Lavender: SNORT is popular Network Intrusion Detection System (NIDS) tool that currently uses a custom rule based system to identify attacks. This presentation emphasizes on writing the algorithm to write generate the rules through GA and the integration of them into nProbe, a similar network monitoring tool written by Luca Deri with a plug-in architecture. Genetic Algorithms are dependent upon identifying attributes to describe a problem and evolving a desired population. In this case, the problem is an attack through the network and identifying the attack through connection property attributes. Genetic Algorithms depends upon training data. DARPA datasets provide training data, in categorized format (attack vs. normal) along with a corresponding raw network recorded format called tcpdump. nProbe has a plug-in architecture allowing for customization. This presentation explains original code in C to evolve rules. It uses the same chromosome attributes used by Gong. The development verifies and contrasts against the research performed by Gong. It also presents the code for integration into nProbe. Don't miss an upload! Subscribe! http://goo.gl/szEauh Stay Connected to O'Reilly Media by Email - http://goo.gl/YZSWbO Follow O'Reilly Media: http://plus.google.com/+oreillymedia https://www.facebook.com/OReilly https://twitter.com/OReillyMedia
Views: 2211 O'Reilly
Support Vector Machine (SVM) - Fun and Easy Machine Learning
 
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Support Vector Machine (SVM) - Fun and Easy Machine Learning https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples. To understand SVM’s a bit better, Lets first take a look at why they are called support vector machines. So say we got some sample data over here of features that classify whether a observed picture is a dog or a cat, so we can for example look at snout length or and ear geometry if we assume that dogs generally have longer snouts and cat have much more pointy ear shapes. So how do we decide where to draw our decision boundary? Well we can draw it over here or here or like this. Any of these would be fine, but what would be the best? If we do not have the optimal decision boundary we could incorrectly mis-classify a dog with a cat. So if we draw an arbitrary separation line and we use intuition to draw it somewhere between this data point for the dog class and this data point of the cat class. These points are known as support Vectors – Which are defined as data points that the margin pushes up against or points that are closest to the opposing class. So the algorithm basically implies that only support vector are important whereas other training examples are ‘ignorable’. An example of this is so that if you have our case of a dog that looks like a cat or cat that is groomed like a dog, we want our classifier to look at these extremes and set our margins based on these support vectors. ----------- www.ArduinoStartups.com ----------- To learn more on Augmented Reality, IoT, Machine Learning FPGAs, Arduinos, PCB Design and Image Processing then Check out http://www.arduinostartups.com/ Please like and Subscribe for more videos :)
Views: 75086 Augmented Startups
Detecting Phishing Websites using Machine Learning Technique
 
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Get this project at http://nevonprojects.com/detecting-phishing-websites-using-machine-learning/ In order to detect and predict phishing website, we proposed an intelligent, flexible and effective system that is based on using classification Data mining algorithm
Views: 8228 Nevon Projects
Data Mining Projects in Java | Data Mining Thesis in Java | Data Mining Code Projects in Java
 
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Contact Best Matlab Simulation Projects Visit us: http://matlabsimulation.com/
Views: 113 matlab simulation
research paper on genetic algorithm in data mining
 
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Order now: https://goo.gl/TIo1T2?85794
WEKA API 7/19: Attribute Selection
 
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To access the code go to the Machine Learning Tutorials Section on the Tutorials page here: http://www.imperial.ac.uk/people/n.sadawi Using WEKA in java
Views: 9514 Noureddin Sadawi
Machine Learning and Pattern Recognition for Algorithmic Forex and Stock Trading: Intro
 
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Welcome to the Machine Learning for Forex and Stock analysis and algorithmic trading tutorial series. In this series, you will be taught how to apply machine learning and pattern recognition principles to the field of stocks and forex. The file: http://sentdex.com/GBPUSD.zip This is especially useful for people interested in quantitative analysis and algo trading. Even if you are not, the series will still be of great use to anyone interested in learning about machine learning and automatic pattern recognition, through a hands-on tutorial series. Sentdex.com Facebook.com/sentdex Twitter.com/sentdex
Views: 155213 sentdex
PGC204 - ECJ (Evolutionary Computation Java) e WEKA
 
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Trabalho de reconhecimento de padrões do curso de ciências da computação na Universidade Federal de Uberlândia (UFU) utilizando as bibliotecas ECJ (Evolutionary Computation Java) e o WEKA. Projeto (SVN): https://code.google.com/p/pgc204/ Artigo: http://pt.scribd.com/doc/152654627/Uma-Comparacao-de-Classificadores-para-Contorno-de-Imagens-de-Folhas Blog: http://wpattern.com Post: http://wpattern.com/blog/post/2013/07/08/ECJ-e-WEKA-(Reconhecimento-de-Padroes).aspx
Views: 2144 Augusto Branquinho
How kNN algorithm works
 
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In this video I describe how the k Nearest Neighbors algorithm works, and provide a simple example using 2-dimensional data and k = 3.
Views: 328209 Thales Sehn Körting
Java Implementation of K-Nearest Neighbors (kNN) Classifier 1/2
 
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The code can be found here: www.imperial.ac.uk/people/n.sadawi Go to Tutorials and then Machine Learning section!
Views: 31059 Noureddin Sadawi
Time Series Data Mining Forecasting with Weka
 
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I am sorry for my poor english. I hope it helps you. when i take the data mining course, i had searched it but i couldnt. So i decided to share this video with you.
Views: 20372 Web Educator
Weka Tutorial 10: Feature Selection with Filter (Data Dimensionality)
 
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This tutorial shows how to select features from a set of features that performs best with a classification algorithm using filter method.
Views: 62651 Rushdi Shams
Linear Genetic Programming in Python Bytecode
 
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In this video Linear Genetic Programming and Python Bytecode is explained by a PhD student.
Views: 61 Programming Myths
Backpropagation in 5 Minutes (tutorial)
 
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Let's discuss the math behind back-propagation. We'll go over the 3 terms from Calculus you need to understand it (derivatives, partial derivatives, and the chain rule and implement it programmatically. Code for this video: https://github.com/llSourcell/how_to_do_math_for_deep_learning Please Subscribe! And like. And comment. That's what keeps me going. I've used this code in a previous video. I had to keep the code as simple as possible in order to add on these mathematical explanations and keep it at around 5 minutes. More Learning resources: https://mihaiv.wordpress.com/2010/02/08/backpropagation-algorithm/ http://outlace.com/Computational-Graph/ http://briandolhansky.com/blog/2013/9/27/artificial-neural-networks-backpropagation-part-4 https://jeremykun.com/2012/12/09/neural-networks-and-backpropagation/ https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/ Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Forgot to add my patron shoutout at the end so special thanks to Patrons Tim Jiang, HG Oh, Hoang, Advait Shinde, Vijay Daniel & Umesh Rangasamy Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
Views: 123073 Siraj Raval
Data Mining Project (ITS665) - Chronic Kidney Disease Dataset
 
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Background music : Polaroid - Sakura Band
Views: 114 Shinhayaro
Using Genetic Algorithms for Network Intrusion Detection and Integration into nProbe
 
05:38
SNORT is popular Network Intrusion Detection System (NIDS) tool that currently uses a custom rule based system to identify attacks. This presentation emphasizes on writing the algorithm to write generate the rules through GA and the integration of them into nProbe, a similar network monitoring tool written by Luca Deri with a plug-in architecture. Genetic Algorithms are dependent upon identifying attributes to describe a problem and evolving a desired population. In this case, the problem is an attack through the network and identifying the attack through connection property attributes. Genetic Algorithms depends upon training data. DARPA datasets provide training data, in categorized format (attack vs. normal) along with a corresponding raw network recorded format called tcpdump. nProbe has a plug-in architecture allowing for customization. This presentation explains original code in C to evolve rules. It uses the same chromosome attributes used by Gong. The development verifies and contrasts against the research performed by Gong. It also presents the code for integration into nProbe.
Views: 5371 IgniteOSCON
Weka Tutorial 09: Feature Selection with Wrapper (Data Dimensionality)
 
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This tutorial shows you how you can use Weka Explorer to select the features from your feature vector for classification task (Wrapper method)
Views: 61808 Rushdi Shams
Grouping Algorithm
 
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Description found at https://sites.google.com/a/lwhs.org/lwhs-computing-2-spring-16/algorithms-projects/ruby-landau-pincus-grouping-algorithm
Views: 167 Ruby Landau-Pincus
Weka JAVA Data Mining Tool (01)
 
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http://www.zaneacademy.com | Waikato Environment for Knowledge Analysis (Weka) download, install, and test run
Views: 329 ZA Data Mining
Predictive Genetic Algorithim
 
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This was a video response to the genetic algorithm videos you posted. I would like to tell you about my project of combining computer science with genomics. Is it possible for a computer or Artificial Intelligence to predict genotype based on phenotype? It was dinner time at home, so please excuse all the kitchen noises.
Views: 121 titanoboa100
Visualization of a Deep Learning Algorithm for Mining Patterns in Data
 
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A 3D graph visualization of a pattern recognition algorithm that uses genetic inheritance to generate a binary decision tree that recognizes bits in a stream of data. This example trains on two arbitrarily chosen sentences represented as an encoded stream of bits. Starting at the root node the tree continues to grow by analyzing the probability of training data matching expectations of the path from the root node to a leaf node. Visualization created using UbiGraph. Algorithm created in Java. Persistency and traversal API provided by Neo4j graph database.
Views: 10029 Kenny Bastani
Data Mining platform with JavaEE
 
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Première plateforme dédiée au Data Mining implémentée avec JavaEE réalisée par Mohamed Heny Selmi
Views: 343 Mohamed Heny SELMI
INTRODUCTION TO DATA MINING IN HINDI
 
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find relevant notes at-https://viden.io/
Views: 96341 LearnEveryone
Genetic Disorder Prediction Tool
 
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This java app will be able to predict the genetic disorder you may be suffering or may suffer in future by matching genes through efficient algorithms
Views: 98 Prasoon Dwivedi
back propagation Neural Network
 
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back propagation Neural Network or Error back propagation Neural Network
Views: 9627 Sanjay Pathak
Genetic algorithms 'n stuff!
 
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my first attempt at a genetic algorithm -- Watch live at https://www.twitch.tv/simuleios
Views: 48 simuleios
Twitter Sentiment Analysis - Learn Python for Data Science #2
 
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In this video we'll be building our own Twitter Sentiment Analyzer in just 14 lines of Python. It will be able to search twitter for a list of tweets about any topic we want, then analyze each tweet to see how positive or negative it's emotion is. The coding challenge for this video is here: https://github.com/llSourcell/twitter_sentiment_challenge Naresh's winning code from last episode: https://github.com/Naresh1318/GenderClassifier/blob/master/Run_Code.py Victor's Runner up code from last episode: https://github.com/Victor-Mazzei/ml-gender-python/blob/master/gender.py I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ More on TextBlob: https://textblob.readthedocs.io/en/dev/ Great info on Sentiment Analysis: https://www.quora.com/How-does-sentiment-analysis-work Great sentiment analysis api: http://www.alchemyapi.com/products/alchemylanguage/sentiment-analysis Read over these course notes if you wanna become an NLP god: http://cs224d.stanford.edu/syllabus.html Best book to become a Python god: https://learnpythonthehardway.org/ Please share this video, like, comment and subscribe! That's what keeps me going. Feel free to support me on Patreon: https://www.patreon.com/user?u=3191693 Two Minute Papers Link: https://www.youtube.com/playlist?list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
Views: 206620 Siraj Raval
Intrusion Detection based on KDD Cup Dataset
 
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Final Presentation for Big Data Analysis
Views: 6575 Qiankun Zhuang
weka j48 classification tutorial
 
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This is a tutorial for the Innovation and technology course in the ePC-UCB. La Paz Bolivia
Views: 48835 Alejandro Peña
(ML 2.1) Classification trees (CART)
 
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Basic intro to decision trees for classification using the CART approach. A playlist of these Machine Learning videos is available here: http://www.youtube.com/my_playlists?p=D0F06AA0D2E8FFBA
Views: 96073 mathematicalmonk
A Secured System for Information Hiding in Image Steganography using Genetic Algorithm and Cryptogra
 
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A Secured System for Information Hiding in Image Steganography using Genetic Algorithm and Cryptography Abstract Encryption is used to securely communicate data in open networks. Each type of data has its own structures; therefore according to the data the different techniques should be used to defend confidential data. Among them digital images are also very popular to carry confidential information in untrusted networks. . For pleasing the defense of data hiding and communication over network, the proposed system uses cryptographic algorithm along with Steganography. In the proposed system, the file which user want to make secure is firstly compressed to shrink in size and then the compressed data is altered into cipher text by using AES cryptographic algorithm and then the encrypted data is concealed in the image. In order to hide the information over the image in complex manner the genetic algorithm based technique is implemented which is used to evaluate the valuable pixels where the data can be hide in a secure manner. In addition of that, for hiding the information in images, the LSB (least significant bits) based steganographic method is used after the selection of eligible pixels. The implementation of the anticipated technique is performed using JAVA technology and for performance evaluation the time and space complexity is computed. In addition of that a comparative study of the proposed technique using the image steganographic technique is also performed in terms of PSNR and MSE. According to the computed performance the proposed technique is adoptable for hiding information in image securely additionally that consumes less space complexity.
Views: 138 1 Crore Projects
JAVA JDBC Tutorial 4- Modification of java code for retrieving data from database
 
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https://www.facebook.com/arshathshameer MyBlog : https://thenewbosten.blogspot.com/
Views: 3302 Techies Coding Arena
How to use ga algorithm in MATLAB-Part I
 
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From this lecture, you can learn how to use ga algorithm provided from MATLAB 2012a or later versions without understanding the concept of genetic algorithm.
Views: 66589 李政軒
Final Year Projects 2015 | Predicting the Analysis of Heart Disease Symptoms
 
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Including Packages ===================== * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 4454 ClickMyProject
How Machine Learning system works Part-2
 
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This video will explain working of machine learning training and testing system. Example Microsoft out look how machine learning system can be used for classification of email.
Views: 2163 MyStudy