程序代写接单-MATH 569 Statistical Learning Spring 2022

MATH 569 Statistical Learning Spring 2022  Topics of Your Project The objective of a class project is to help you gain experience with research, and to relate what you learn to real life problems which may require you learn new techniques (or develop new methods by yourself). You are expected to submit a summary report at the end of the semester. Below are two types of possible projects (you only need to choose one of them). 1. Solving a real life problem. A typical report includes problem formulation, data analysis, proposed solutions, and interpretation of results. The data set can be from your own research or the public domain. 2. Numerical study of statistical methods/models using existing data sets in the literature. Ideally your approach is substantially different from those in the literature, but it will be all right if you repeat the analysis as long as you did independently. Some examples are • Compare performance of competitive statistical (or data mining) techniques; • Ask different questions or investigate new ideas of statistical methods or models; • Identify optimal parameters of speci c statistical methods or models. Note that the crucial aspect of your project is to analyze some data sets, not using some specific statistical methods or models we discussed in class. Datasets: You can collect the data by yourself, use the data set from your own research or the public domain. The followings are some examples of online datasets (you can use google or other search engineer to find more): 1. http://www.quandl.com/ (financial and economic time-series datasets) 2. https://datamarket.com/topic/list/ (a privately held Icelandic company that specializes in providing access to data from public, and, to a lesser extent, private institutions and companies.) 3. http://kdd.ics.uci.edu/ or http://archive.ics.uci.edu/ml/ One example is the KDD cup 1999 data at http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html More KDD cup data can be found at http://www.sigkdd.org/kddcup/index.php 4. http://lib.stat.cmu.edu/DASL/ 5. http://www.kdnuggets.com/datasets/index.html (links to more data repositories.) 6. Data from literature, such as journals Journal of American Statistical Association, Journal of Royal Statistical Society: Series B, Statistica Sinica, Annals of Applied Statistics, Journal of Computational and Graphical Statistics, etc. To inspire your projects, some concrete examples can be as follows: • analyze some data sets in some competitions, see the links http://www.kaggle.com/competitions • model data from some government websites such as http://www.cdc.gov/biosense/correlate/ or http: //www.ngdc.noaa.gov/stp/satellite/goes/dataaccess.html • know aspect of Chicago through Chicago Data Portal https://data.cityofchicago.org/ 1

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