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Comparative Analysis of Decision Tree Approaches

$250-750 USD

Cancelled
Posted over 10 years ago

$250-750 USD

Paid on delivery
This Project requires to compare at least 6 different decision tree algorithms (both standard ones and relatively new ones) to use in prediction of bankruptcy. The algorithms can be compared using Weka, IBM Modeler or via other softwares. Each algorithm will be compared on well-known evaluation metrics, such asprecision, recall, F-measure, ROC curve, mean absoluate error, etc. For a sample publication please look: [login to view URL] * The datasets for the study are Australian, German, Japanese bankruptcy datasets.
Project ID: 5180385

About the project

5 proposals
Remote project
Active 10 yrs ago

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5 freelancers are bidding on average $493 USD for this job
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Hi I am ready to do the job. I have more than 10 years experience data warehousing and data mining experience. Thanks.
$555 USD in 10 days
4.9 (3 reviews)
3.3
3.3
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I have the experience to complete this project. A master degree in Data mining and Artificial Intelligence algorithms with a bachelor in Math And physics background. Please provide more details to my mail. thanks Best regards
$399 USD in 8 days
4.8 (2 reviews)
1.6
1.6
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I have done much research work on Decision tree learning and can provide you this review document. Looking forward to discuss details.
$400 USD in 8 days
0.0 (0 reviews)
0.0
0.0
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Hi, if you still don't find anyone help you, I think I am that guy you are looking for. I am PhD student for Machine learning, and I am familiar with decision tree, neural network, deep learning, etc. Actually, I have several papers on this. Please let me know more detail, if you want to me help you. Thanks.
$555 USD in 6 days
0.0 (0 reviews)
0.0
0.0
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Sir/Madam, Greetings. This is a Bioinformatician. Yes , I have interacted with numerous algorithms being in this field. Let me know your utmost budget and deadline Regards Nafeesa Mazhar
$555 USD in 7 days
0.0 (0 reviews)
0.0
0.0

About the client

Flag of TURKEY
1, Turkey
4.7
20
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Member since Mar 27, 2011

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