PPT-Supervised Learning Regression, Classification

Linear regression k NN classification Debapriyo Majumdar Data Mining Fall 2014 Indian Statistical Institute Kolkata August 11 2014 An Example Size of Engine vs Power 2 Engine displacement cc. Data Mining/Machine Learning Algorithms for Business Intelligence. Dr. Bambang Parmanto. Extraction Of Knowledge From Data. DSS Architecture: Learning and Predicting. Courtesy: Tim Graettinger. Data Mining: Definitions. Ashwath Rajan. Overview, in brief. Marriage between statistics, linear algebra, calculus, and computer science. Machine Learning:. Supervised Learning. ex: linear Regression. Unsupervised Learning. ex: clustering. Machine Learning. Last Time. Support Vector Machines. Kernel Methods. Today. Review . of Supervised Learning. Unsupervised . Learning . (. Soft) K-means clustering. Expectation Maximization. Spectral Clustering. Several slides from . Luke . Xettlemoyer. , . Carlos . Guestrin. and Ben . Taskar. Typical Paradigms of Recognition. Feature Computation. Model. Visual Recognition. Identification. Is this your car?. scikit. -learn. http://scikit-learn.org/stable/. scikit. -learn. Machine Learning in Python. Simple . and efficient tools for data mining and data analysis. Built . on . NumPy. , . SciPy. , and . matplotlib. 01/24/2012. Agenda. 0. Introduction of machine . learning. --Some clinical examples. Introduction . of classification. 1. Cross validation. 2. . Over-fitting. Feature (gene) selection. Performance assessment. Walker Wieland. GEOG 342. Introduction. Isocluster. Unsupervised. Interactive Supervised . Raster Analysis. Conclusions. Outline. GIS work, watershed analysis. Characterize amounts of impervious cover (IC) at spatial extents . Learn . About You.. Luke K. McDowell. U.S. Naval Academy. http://www.usna.edu/Users/cs/lmcdowel. . Joint work with:. MIDN Josh King, USNA. David Aha, NRL. Bio. 1993-1997: Princeton University. B.S.E., Electrical Engineering. An Overview of Machine Learning Speaker: Yi-Fan Chang Adviser: Prof. J. J. Ding Date : 2011/10/21 What is machine learning ? Learning system model Training and testing Performance Algorithms Machine learning Learning What is learning? What are the types of learning? Why aren’t robots using neural networks all the time? They are like the brain, right? Where does learning go in our operational architecture? Machine Learning. Classification. Email: Spam / Not Spam?. Online Transactions: Fraudulent (Yes / No)?. Tumor: Malignant / Benign ?. 0: “Negative Class” (e.g., benign tumor). . 1: “Positive Class” (e.g., malignant tumor). USDA Forest Service. Juliette Bateman (she/her). Remote Sensing Specialist/Trainer, . juliette.bateman@usda.gov. Soil Mapping and Classification in Google Earth Engine. Day 2:. Supervised and Unsupervised Classifications. Outline. Regression vs. Classification. Two . Basic Methods: Linear Least Square vs. Nearest Neighbors. C. lassification via Regression. C. urse of Dimensionality and . M. odel Selection. G. eneralized Linear Models and Basis Expansion. Er. . . Mohd. . Shah . Alam. Assistant Professor. Department of Computer Science & Engineering,. UIET, CSJM University, Kanpur. Agenda. What is Machine Learning?. How Machine learning . is differ from Traditional Programming?.