Data classifiers työt

Need someone who is skilled in matlab and mathematics. The questions to be answered have been attached. Each question should be answered in a seperate M-File and commented appropriately. All code should be done by hand, no using matlabs built in statistics libraries / packages!

Need someone who is skilled in matlab and mathematics / data set classifiers. The questions to be answered have been uploaded. Each question should be done in a seperate M-File and commented appropriatley. All coding must be done manually, matlabs statistics toolbox CANNOT be used! Needs to be done by 31/10/2011.

...the documentation; identify the different types of functions, paying particular attention to the data generation and regression tools. Add noise (from different types) and outliers (from different types) to your data sets and evaluate their impact in the the previous experiments by adding new dimensions (features) to the datasets, and study the impact of : 1) a detailed report ,. It will include tables, graphs, plots, figures and a critical discussion about the results obtained. You will use basic tools for classification in PRTools, and you will apply them to datasets in theUCI Machine Learning Repository. The basic tools will comprise: simple classifiers, bagging strategies, boosting methods, classifier ensembles and kernel approaches. Download and familiarise

...postings Software: MySQL Ruby Rails Any gems, or add-ons need to be bundled with Rails app Contractor will be provided with: Spreadsheet with site name, country, region, sub region, rss/atom feed URL, and region HTML URL. Limited sample code for posting to Wordpress blog using XMLRPC (upon request) ** Completed app should include * All required MySQL tables, data, rails app, any gems, or add-ons need to be bundled with Rails app. * The app should - Parse all urls provided - Discover new posts - Recover from any errors - Estimate categories for each new post using Bayesian filter or other trainable filter meted, - Have training methods for Bayesian filter - Post new posts to weblog with estimated categories - Modify existing p...

...decision trees (for a given dataset) for the tree which will best fit the data. We can consider the "usual" tree learning algorithms as performing a greedy look-ahead search: at each step they choose the split which is the best according to some criteria (ie covering the maximum number of positive examples, maximally reducing the entropy, etc.). "Nearly all decision tree induction algorithms create a single decision tree based upon local information of how well a feature partitions the training data" (Murphy and Pazzani, 1994). The purpose of this project is to code a best-first seach algorithm in the space of possible decision trees. This approach has exponential run-time respectively to the number of attributes (data object descriptors) so ...

...call. The DLL will be called from Labview, images will be both color and gray scale, and will be passed in via pointer. Images are allocated in Labview, no image management is necessary, aside from any temporary images needed by the classifier. The Labview system will need to specify which set of classifiers to use, the classifier main function will need to return an array of scores- how likely on a scale of 0-1000 that the current image contains a match within the specified set of classifiers specified. For instance, if the user selects as the classifier file, and the labview image passed in contains eyes, it will return an array of positions, size, and score of each eye found in the image. If none, then NULL is returned. The de-initializer function shall take care...

In the classification problem of two classes, two sets of vector characteristics are provided, one for each class. The sets ar...classified in the Class with the most impressions. B) Out of the 20 characteristics of the problem, select 3 (your choice). From each data set select randomly 60% of the vectors as training vectors and use the rest to find the classification error, according to the algorithm k-NN (k = 1 and k = 3). Repeat the above process of random choice of the 60% of the vectors 10 times and calculate the average classification error for k = 3. C) Instead of classifier k-NN, construct and train a neural network of your choice with the same 3 characteristics you selected in (B). Then proceed as in (B) and comment/compare the performance of the ...

In the classification problem of two classes, two sets of vector characteristics are provided, one for each class. The sets ar...classified in the Class with the most impressions. B) Out of the 20 characteristics of the problem, select 3 (your choice). From each data set select randomly 60% of the vectors as training vectors and use the rest to find the classification error, according to the algorithm k-NN (k = 1 and k = 3). Repeat the above process of random choice of the 60% of the vectors 10 times and calculate the average classification error for k = 3. C) Instead of classifier k-NN, construct and train a neural network of your choice with the same 3 characteristics you selected in (B). Then proceed as in (B) and comment/compare the performance of the ...

Description This project is about preprocessing method in data mining using machine learning knowledge. I m trying to use C++ programming since the basic coding of the three algorithms which used to do discretization is in C++. The three algorithms are Equal Frequency Binning, Ent-MDLP and Boolean Reasoning. I m using all these 3 methods to enhance learning process through two classifiers. Those two classifiers are Rough Set and Neural Network Classifiers. This project is to determine which classifier is better within the three algorithms. Which algorithm is more accurate and better to be used in which classifier? Willing to pay USD 100. Anyone interested please mail me for more details. I will able to give more description.

This project is about preprocessing method in data mining using machine learning knowledge. I m trying to use C++ programming since the basic coding of the three algorithms which used to do discretization is in C++. The three algorithms are Equal Frequency Binning, Ent-MDLP and Boolean Reasoning. I m using all these 3 methods to enhance learning process through two classifiers. Those two classifiers are Rough Set and Neural Network Classifiers. This project is to determine which classifier is better within the three algorithms. Which algorithm is more accurate and better to be used in which classifier? Willing to pay USD 100. Anyone interested please mail me for more details. I will able to give more description.

In C, C++? or Matlab: a program that detects a human face and recognizes facial emotions. A real time system that detects a human face and then, based on other algoritms and other? classifiers, recognize an emotion. The result is displayed in percents Input: a picture or a video stream(webcam, movie etc) Output: the same picture, but? overall the face recognized underlined and the expression in percent bars. ## Deliverables We must talk about the? algorithms used in the program: the face detection and the emotion recognition. I need minimum 2? algorithms for the emotion recognition (because I'll make a comparasion of the results after)

I simply need 100? **opencv**-**haar**-**classifier** xml files found anywhere on the web. They must be unique and eacy one identifes a? different object. You can train them your self or find 100 of them on the web. There is no more to? clarify about this job? requirement, I simply need 100 unique? opencv-haar-classifiers. ## Deliverables Please zip your? **opencv**-**haar**-**classifier**? xml files either into one zip or into multiple zips as you find or train them.

You will be required to program in Java - you have a choice of modifying on existing programs or re-write your own if you wish. The candidates will also need to have relatively good experience/skill with? Data Mining / Machine Learning. If so, please read on. ## Deliverables The design of this? project? is and will be required to? based on the following paper: <> Please have a look at this first as it will give you an idea of what will be expected. Please note you? won't be required? to add all of the features on the above paper? for the NEC part? but only the important ones(around 3 features). You will need to? post daily updates on progress and subtask completion, this is strictly required for the project. Please note this

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I need to have some classifiers integrated in the OpenCV sample so that I achieve a software like the one shown in the attached textfile. There are some videos in the attached textfile as well. I hope it's an easy work for somebody who has worked with OpenCV already. We will need to discuss some more, but if you're interested, please post a bid first. ## Deliverables 1) Complete and fully-functional working program(s) in executable form as well as complete source code of all work done. 2) Deliverables must be in ready-to-run condition, as follows (depending on the nature of the deliverables): a) For web sites or other server-side deliverables intended to only ever exist in one place in the Buyer's environment--Deliverables must be installed by the Seller in r...

Hello Iam making an application for Face Detection for privacy protection. I have already implemented a Graphical User Inteface in Visual Studio c++ in combination wi...the face have taken place the application applys a blur filter around the face to keep it hidden. What i would like is someone to train a classifier for me that will detect Rotated faces too. I want to use the PIE database with positives pictures that can be found here: <> The database can be downloaded for free. Information on training classifiers: <> ## Deliverables 1)An XML() trained classifier that can be integrated into OPENCV and detect rotated faces with a good accuracy. ## Platform Windows XP

...from true and false data. Once the program is trained and learns the rules (these are called classifiers) we can give the program to read a new sequence and score it accordingly. training Input: gaggtatgttcagtgagtcaggtattcctggtgagtgaggtgagc training Output (it is the same as the input but it splits in rows.): gaggtatgt tcagtgagt caggtattc ctggtgagt gaggtgagc It is like this just to get the idea: Given that 123456 is correct and 214536 is wrong. The selection criteria is 45. If I give you 124456. Is it true or false? By just looking you can give an estimate or a percentage that it is true. If I give you 11111111112345633333333 the program must find the pattern 123456 and score it 100% correct because it is exactly the same as the training ...

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A fully-working, clearly-coded C++ script (about 1,000 lines including comments) using standard libraries to be adapted to accept a new form of dataset. It functions to classify documents using neural networks and bayesian methods. Basic knowledge of classifiers with specialty in these two is required although the classifiers have all been implemented already and no further implementation is necessary. I require some minor modifications to be done to the text processing which should be really easy but I'm lacking the time to do so. The code has been almost fully commented, I would just require some clarification on a few portions of it. And most important (the focus of this project), I would like the code to be refactored at the end for speed (target of one and a half ti...

This project deals with classification of images. You are given 2000 images with Image IDs varying from 0 to 1999. They belong to the following 20 categories: **1. Design image classifiers using the provided features. Note that the subtlety is that the learning problem isnot a standard “supervised learning?? problem because you are only given labels of images (not labels forregions).** **2. Design image classifiers using your own features.** **3. For each image category, you need to randomly pick 50 images as training data. So the whole training setshould have 1000 images; and the test set has 1000 images. ** **4. Repeat training and testing for 10 different randomizations. Report the average training accuracy, standarddeviation of training accuracies, test...

...locations such as North info, southern info, information on each provence, and highly detailed information on each city. When I add a city to the website, I imagine that I can assign classifiers to it. So if I add a city I might choose "city" "Mountains" "Jungle" "beaches" etc to it so that when someone clicks on "beaches" they will get a listing with all of the places that have that classifer. This might be accomplished using some kind of tagging system that only the admin can use. I also imagine that each location will have little icons representing these classifiers on their main information page. So when someone is looking at a specific location they can see right away little icons representing the various featu...