[View Context].Rudy Setiono. [View Context].Rudy Setiono and Huan Liu. Additionally, some of the datasets on this list include sample regression tasks for you to complete with the data. 1999. CoRR, csLG/0211003. [View Context].Paul D. Wilson and Tony R. Martinez. 9. breast-quad: left-up, left-low, right-up, right-low, central. Characterization of the Wisconsin Breast cancer Database Using a Hybrid Symbolic-Connectionist System. [View Context].Fei Sha and Lawrence K. Saul and Daniel D. Lee. PAKDD. 2001. The OLS regression challenge tasks you with predicting cancer mortality rates for US counties. A. K Suykens and Guido Dedene and Bart De Moor and Jan Vanthienen and Katholieke Universiteit Leuven. [View Context].Iñaki Inza and Pedro Larrañaga and Basilio Sierra and Ramon Etxeberria and Jose Antonio Lozano and Jos Manuel Peña. 1998. [View Context].Ismail Taha and Joydeep Ghosh. Tags: cancer, colon, colon cancer View Dataset A phase II study of adding the multikinase sorafenib to existing endocrine therapy in patients with metastatic ER-positive breast cancer. 2000. 2004. Rev, 11. [View Context].Pedro Domingos. data = load_breast_cancer() chevron_right. 2000. Explore and run machine learning code with Kaggle Notebooks | Using data from Breast Cancer Wisconsin (Diagnostic) Data Set [View Context].Chotirat Ann and Dimitrios Gunopulos. UEPG, CPD CEFET-PR, CPGEI PUC-PR, PPGIA Praa Santos Andrade, s/n Av. [View Context].David M J Tax and Robert P W Duin. [View Context].Geoffrey I Webb. [View Context].Rong-En Fan and P. -H Chen and C. -J Lin. Department of Computer Methods, Nicholas Copernicus University. The data is in a CSV file which includes the following columns: model, year, selling price, showroom price, kilometers driven, fuel type, seller type, transmission, and number of previous owners. Knowl. [View Context].Kaizhu Huang and Haiqin Yang and Irwin King and Michael R. Lyu and Laiwan Chan. (See also lymphography and primary-tumor.) [View Context].Saher Esmeir and Shaul Markovitch. Department of Mathematical Sciences The Johns Hopkins University. School of Computing and Mathematics Deakin University. [View Context].G. Sete de Setembro, 3165. ECML. 3. menopause: lt40, ge40, premeno. Department of Computer Science, Stanford University. This dataset was inspired by the book Machine Learning with R by Brett Lantz. [View Context].Wl/odzisl/aw Duch and Rafal/ Adamczak Email:duchraad@phys. [View Context].Ayhan Demiriz and Kristin P. Bennett and John Shawe and I. Nouretdinov V.. 2002. 8. breast: left, right. Artificial Intelligence in Medicine, 25. [View Context].W. [View Context].Michael R. Berthold and Klaus--Peter Huber. Induction in Noisy Domains. ICML. Basser Department of Computer Science The University of Sydney. An evolutionary artificial neural networks approach for breast cancer diagnosis. [View Context].M. [View Context].Christophe Giraud and Tony Martinez and Christophe G. Giraud-Carrier. Modeling for Optimal Probability Prediction. 2002. 37 votes. 4. tumor-size: 0-4, 5-9, 10-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59. Discovering Comprehensible Classification Rules with a Genetic Algorithm. [View Context].Jarkko Salojarvi and Samuel Kaski and Janne Sinkkonen. 1995. Usage: Classify the type of cancer… A. Galway and Michael G. Madden. 2000. [View Context].Kristin P. Bennett and Ayhan Demiriz and John Shawe-Taylor. From sentiment analysis models to content moderation models and other NLP use cases, Twitter data can be used to train various machine learning algorithms. The LSS Non-cancer Condition dataset (~10,900, one record per condition) contains information on non-cancer conditions diagnosed near the time of lung cancer diagnosis or of diagnostic evaluation for lung cancer … The University of Birmingham. Department of Computer Science University of Massachusetts. ICML. 1995. Robust Ensemble Learning for Data Mining. [View Context].W. Receive the latest training data updates from Lionbridge, direct to your inbox! Capturing enough accurate, quality data at scale is a common challenge for individuals and businesses alike. Data. For those of you looking to learn more about the topic or complete some sample assignments, this article will introduce open linear regression datasets you can download today. Hybrid Extreme Point Tabu Search. Popular Ensemble Methods: An Empirical Study. IEEE Trans. Institut fur Rechnerentwurf und Fehlertoleranz (Prof. D. Schmid) Universitat Karlsruhe. Proceedings of ANNIE. Introduction. [View Context].Adil M. Bagirov and Alex Rubinov and A. N. Soukhojak and John Yearwood. In this short post you will discover how you can load standard classification and regression datasets in R. This post will show you 3 R libraries that you can use to load standard datasets and 10 specific datasets that you can use for machine learning in R. It is invaluable to load standard datasets in CEFET-PR, CPGEI Av. Igor Fischer and Jan Poland. 2000. The instances are described by 9 attributes, some of which are linear … & Niblett,T. link. [1] Papers were automatically harvested and associated with this data set, in collaboration 1. [View Context].Hussein A. Abbass. pl. of Decision Sciences and Eng. Lucas is a seasoned writer, with a specialization in pop culture and tech. Intell. of Mathematical Sciences One Microsoft Way Dept. (JAIR, 11. [View Context].John G. Cleary and Leonard E. Trigg. 2002. 2004. NIPS. Telecommunications Lab. 1995. Department of Computer Methods, Nicholas Copernicus University. [View Context].Charles Campbell and Nello Cristianini. of Decision Sciences and Eng. An Implementation of Logical Analysis of Data. (JAIR, 3. What are some open datasets for machine learning? [View Context].Michael G. Madden. [View Context].Adam H. Cannon and Lenore J. Cowen and Carey E. Priebe. KDD. Using this data, you can experiment with predictive modeling, rolling linear regression, and more. The data contains 2938 rows and 22 columns. [View Context]. Online Bagging and Boosting. This breast cancer domain was obtained from the University Medical Centre, Institute of … [View Context].Geoffrey I. Webb. [View Context].Rong Jin and Yan Liu and Luo Si and Jaime Carbonell and Alexander G. Hauptmann. [View Context].Huan Liu and Hiroshi Motoda and Manoranjan Dash. Smooth Support Vector Machines. Machine Learning, 24. Simple Learning Algorithms for Training Support Vector Machines. 1998. [View Context].Yongmei Wang and Ian H. Witten. Analysing Rough Sets weighting methods for Case-Based Reasoning Systems. School of Computing and Mathematics Deakin University. Applied Economic Sciences. OPUS: An Efficient Admissible Algorithm for Unordered Search. Enginyeria i Arquitectura La Salle. This breast cancer domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. Microsoft Research Dept. 2000. This is one of three domains provided by the Oncology Institute that has repeatedly appeared in the machine learning literature. A. J Doherty and Rolf Adams and Neil Davey. National Science Foundation. 2000. [View Context].David W. Opitz and Richard Maclin. Australian Joint Conference on Artificial Intelligence. Dept. Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines. [View Context].Lorne Mason and Peter L. Bartlett and Jonathan Baxter. Data Eng, 12. 2002. [View Context].Maria Salamo and Elisabet Golobardes. Arc: Ensemble Learning in the Presence of Outliers. Thanks go to M. Zwitter and M. Soklic for providing the data. [View Context].David Kwartowitz and Sean Brophy and Horace Mann. Fast Heuristics for the Maximum Feasible Subsystem Problem. University of Bristol Department of Computer Science ILA: Combining Inductive Learning with Prior Knowledge and Reasoning. Knowl. Dept. 2000. C4.5, Class Imbalance, and Cost Sensitivity: Why Under-Sampling beats Over-Sampling. [View Context].K. A streaming ensemble algorithm (SEA) for large-scale classification. 1998. Evaluation of the Performance of the Markov Blanket Bayesian Classifier Algorithm. AAAI/IAAI. [View Context].Rafael S. Parpinelli and Heitor S. Lopes and Alex Alves Freitas. Lionbridge is a registered trademark of Lionbridge Technologies, Inc. Sign up to our newsletter for fresh developments from the world of training data. ICANN. Nick Street and Yoo-Hyon Kim. From the UCI Machine Learning Repository, this dataset can be used for regression modeling and classification tasks. Symbolic Interpretation of Artificial Neural Networks. I am looking for a dataset with data gathered from African and African Caribbean men while undergoing tests for prostate cancer. Institute for Information Technology, National Research Council Canada. [View Context].Endre Boros and Peter Hammer and Toshihide Ibaraki and Alexander Kogan and Eddy Mayoraz and Ilya B. Muchnik. Sys. Breast Cancer… IJCAI. Abstract: Lung cancer … [View Context].Karthik Ramakrishnan. This dataset contains information compiled by the World Health Organization and the United Nations to track factors that affect life expectancy. Lionbridge brings you interviews with industry experts, dataset collections and more. Nick Street. Session S2D Work In Progress: Establishing multiple contexts for student's progressive refinement of data mining. 2002. [View Context].Richard Maclin. [View Context].Rafael S. Parpinelli and Heitor S. Lopes and Alex Alves Freitas. PART FOUR: ANT COLONY OPTIMIZATION AND IMMUNE SYSTEMS Chapter X An Ant Colony Algorithm for Classification Rule Discovery. Preliminary Thesis Proposal Computer Sciences Department University of Wisconsin. Qingping Tao A DISSERTATION Faculty of The Graduate College University of Nebraska In Partial Fulfillment of Requirements. [View Context].. Prototype Selection for Composite Nearest Neighbor Classifiers. [View Context].Bernhard Pfahringer and Geoffrey Holmes and Richard Kirkby. Support vector domain description. Res. [View Context].Jennifer A. Progress in Machine Learning, 31-45, Sigma Press. [View Context].Sally A. Goldman and Yan Zhou. This data set includes 201 instances of one class and 85 instances of another class. 1999. [View Context].Lorne Mason and Jonathan Baxter and Peter L. Bartlett and Marcus Frean. The ANNIGMA-Wrapper Approach to Neural Nets Feature Selection for Knowledge Discovery and Data Mining. Twitter Sentiment Analysis Dataset. Boosted Dyadic Kernel Discriminants. Improved Generalization Through Explicit Optimization of Margins. Journal of Machine Learning Research, 3. Center for Machine Learning and Intelligent Systems: About Citation Policy Donate a Data Set Contact. School of Computing National University of Singapore. This dataset contains 2,77,524 images of size 50×50 extracted from 162 mount slide images of breast cancer … Experiences with OB1, An Optimal Bayes Decision Tree Learner. S and Bradley K. P and Bennett A. Demiriz. 2000. Microsoft Research Dept. Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets… This repository was created to ensure that the datasets … 1999. This dataset includes data taken from cancer.gov about deaths due to cancer in the United States. Built for multiple linear regression and multivariate analysis, the Fish Market Dataset contains information about common fish species in market sales. An Empirical Assessment of Kernel Type Performance for Least Squares Support Vector Machine Classifiers. An Ant Colony Based System for Data Mining: Applications to Medical Data. Experimental comparisons of online and batch versions of bagging and boosting. NIPS. It is in CSV format and includes the following information about cancer in the US: death rates, reported cases, US county name, income per county, population, demographics, and more. J. Artif. Alternatively, if you are looking for a platform to annotate your own data and create custom datasets, sign up for a free trial of our data annotation platform. Even if you have no interest in the stock market, many of the datasets … Constrained K-Means Clustering. We are applying Machine Learning on Cancer Dataset for Screening, prognosis/prediction, especially for Breast Cancer. 2002. [View Context].Bernhard Pfahringer and Geoffrey Holmes and Gabi Schmidberger. Dept. [View Context].Rudy Setiono and Huan Liu. for nominal and -100000 for numerical attributes. The dataset includes the fish species, weight, length, height, and width. A useful dataset for price prediction, this vehicle dataset includes information about cars and motorcycles listed on CarDekho.com. One of three cancer-related datasets provided by the Oncology Institute that appears frequently in machine learning literature. 2002. Assistant-86: A Knowledge-Elicitation Tool for Sophisticated Users. 2001. Example Application – Cancer Dataset The Breast Cancer Wisconsin) dataset included with Python sklearn is a classification dataset, that details measurements for breast cancer recorded … [Web Link] Tan, M., & Eshelman, L. (1988). ICML. 1997. © 2020 Lionbridge Technologies, Inc. All rights reserved. The … Lookahead-based algorithms for anytime induction of decision trees. Unifying Instance-Based and Rule-Based Induction. Res. GMD FIRST, Kekul#estr. Created as a resource for technical analysis, this dataset contains historical data from the New York stock market. Filter By ... Search. [View Context].Gavin Brown. Heterogeneous Forests of Decision Trees. The dataset consists of purchase date, age of property, location, house price of unit area, and distance to nearest station. brightness_4. ICML. [View Context].Erin J. Bredensteiner and Kristin P. Bennett. Computer Science Department University of California. Institute of Information Science. We at Lionbridge have created the ultimate cheat sheet for high-quality datasets. School of Computer Science, Carnegie Mellon University. Control-Sensitive Feature Selection for Lazy Learners. 1997. Boosting Classifiers Regionally. KDD. Extracting M-of-N Rules from Trained Neural Networks. Improved Center Point Selection for Probabilistic Neural Networks. NeuroLinear: From neural networks to oblique decision rules. [View Context].Nikunj C. Oza and Stuart J. Russell. 10. irradiat: yes, no. Combining Cross-Validation and Confidence to Measure Fitness. [View Context].Yuh-Jeng Lee. Recommended to you based on your activity and what's popular • Feedback Wrapping Boosters against Noise. Computational intelligence methods for rule-based data understanding. Using weighted networks to represent classification knowledge in noisy domains. Machine Learning Datasets. 1999. Biased Minimax Probability Machine for Medical Diagnosis. [View Context].Petri Kontkanen and Petri Myllym and Tomi Silander and Henry Tirri and Peter Gr. [View Context].Yk Huhtala and Juha Kärkkäinen and Pasi Porkka and Hannu Toivonen. Machine Learning, 38. 1996. This dataset is taken from OpenML - breast-cancer. A Column Generation Algorithm For Boosting. Department of Computer Science and Information Engineering National Taiwan University. Unsupervised and supervised data classification via nonsmooth and global optimization. In Progress in Machine Learning (from the Proceedings of the 2nd European Working Session on Learning), 11-30, Bled, Yugoslavia: Sigma Press. Randall Wilson and Roel Martinez. Sete de Setembro. [Web Link]. ICDE. Approximate Distance Classification. J. Artif. A Neural Network Model for Prognostic Prediction. I decided to use these datasets because they had all their features in common and shared a similar number of samples. International Collaboration on Cancer Reporting (ICCR) Datasets have been developed to provide a consistent, evidence based approach for the reporting of cancer. Issues in Stacked Generalization. This repository contains a copy of machine learning datasets used in tutorials on MachineLearningMastery.com. "-//W3C//DTD HTML 4.01 Transitional//EN\">, Breast Cancer Data Set ICML. Intell. Cervical cancer is the second leading cause of cancer death in women aged 20 to 39 years. The dataset contains data from cancer.gov, clinicaltrials.gov, and the American Community Survey. [View Context].Bart Baesens and Stijn Viaene and Tony Van Gestel and J. [View Context].Kristin P. Bennett and Erin J. Bredensteiner. Neural-Network Feature Selector. [View Context].Huan Liu. You need standard datasets to practice machine learning. Machine Learning Datasets for Computer Vision and Image Processing. 2000. Accuracy bounds for ensembles under 0 { 1 loss. Breast Cancer Prediction Using Machine Learning. [View Context].Matthew Mullin and Rahul Sukthankar. Learning Decision Lists by Prepending Inferred Rules. Proceedings of the Fifth International Conference on Machine Learning, 121-134, Ann Arbor, MI. Showing 34 out of 34 Datasets *Missing values are filled in with '?' [View Context].Kristin P. Bennett and Ayhan Demiriz and Richard Maclin. A New Boosting Algorithm Using Input-Dependent Regularizer. Department of Computer Science University of Waikato. Department of Information Technology National University of Ireland, Galway. UNIVERSITY OF MINNESOTA. Diversity in Neural Network Ensembles. [View Context].Chiranjib Bhattacharyya. Repository Web View ALL Data Sets: Lung Cancer Data Set Download: Data Folder, Data Set Description. Xtal Mountain Information Technology & Computer Science Department, University of Waikato. For each of the 3 different types of cancer considered, three datasets were used, containing information about DNA methylation (Methylation450k), gene expression RNAseq … Class: no-recurrence-events, recurrence-events 2. age: 10-19, 20-29, 30-39, 40-49, 50-59, 60-69, 70-79, 80-89, 90-99. Generality is more significant than complexity: Toward an alternative to Occam's Razor. of Decision Sciences and Eng. These datasets are then grouped by information type rather than by cancer. 2004. D. MAKING EFFICIENT LEARNING ALGORITHMS WITH EXPONENTIALLY MANY FEATURES. It contains 1338 rows of data and the following columns: age, gender, BMI, children, smoker, region, insurance charges. [View Context].P. 1996. 1999. Representing the behaviour of supervised classification learning algorithms by Bayesian networks. Data Eng, 11. 1999. Intell. In Proceedings of the Fifth National Conference on Artificial Intelligence, 1041-1045, Philadelphia, PA: Morgan Kaufmann. KDD. Every data scientist will likely have to perform linear regression tasks and predictive modeling processes at some point in their studies or career. Working Set Selection Using the Second Order Information for Training SVM. The data contains medical information and costs billed by health insurance companies. of Mathematical Sciences One Microsoft Way Dept. The Multi-Purpose Incremental Learning System AQ15 and its Testing Application to Three Medical Domains.