PDF-Data Preprocessing

Author : luanne-stotts | Published Date : 2015-09-12

1 Mirek Riedewald Some slides based on presentation by Jiawei Han and Micheline Kamber Motivation x2022 Garbage in garbage out x2013 Cannot get good mining results

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Data Preprocessing: Transcript


1 Mirek Riedewald Some slides based on presentation by Jiawei Han and Micheline Kamber Motivation x2022 Garbage in garbage out x2013 Cannot get good mining results from bad data x2022 Ne. : . Coregistration. and Spatial Normalisation. Cassy . Fiford. and . Demis. Kia. Methods for Dummies 2014. With thanks to Gabriel Ziegler. 1. . Preprocessing. Recap. 2. . Coregistration. 3. Spatial Normalisation. . in. i. ncremental. SAT. Alexander Nadel. 1. , . Vadim Ryvchin. 1,2. , and . Ofer. Strichman. 2. 1 – Intel, Haifa, Israel. 2 – Technion, Haifa, Israel. SAT’12, Trento, Italy. Introduction. Data preprocessing Discretization of continuous data Attribute reduction Model establishing of neural network 205 0.2, then If 0.2 0.4, then = 2; If 0.4 0.2, then = 3; If 0.6 0.2, t Methods & models for fMRI data . analysis in . neuroeconomics. 17 April 2010. Klaas Enno Stephan . Laboratory for Social and Neural Systrems Research. Institute for Empirical Research in Economics. Acquisition, preprocessing and analysis of spectra. Raman . spectrometer. . scheme. Acquisition, preprocessing and analysis of Raman spectra. 2. Credits: http://. www.doitpoms.ac.uk. /. tlplib. /. raman. Presenter: Nizar Habash. COMS E6998: Topics in Computer Science: Machine Translation. February 7, 2013. Reading Set #1. Papers Discussed. Nizar Habash and Fatiha Sadat. 2006. . Arabic Preprocessing Schemes for Statistical Machine Translation. 严超赣. Chao-Gan Yan, Ph.D.. yancg@psych.ac.cn. http://. rfmri.org. /. yan. Institute of Psychology, Chinese Academy of Sciences. DPARSF. (Yan and Zang, 2010). 2. Data Processing Assistant for Resting-State fMRI (DPARSF). Ahmedul Kabir. TA, CS 548, Spring 2015. 1. Preprocessing Techniques Covered. Standardization and Normalization. Missing . value . replacement. Resampling. Discretization. Feature . Selection. Dimensionality Reduction: PCA. Learning Objectives. Be . able to describe when and why image corrections are appropriate or . necessary. Give . examples of some common approaches to image . correction. Understand the processing steps of Landsat data. Data cleaning. Data . d. iscretization. Binning. Clustering. Binarization. Data integration. Aggregation. Smoothing. DATA PREPARATION: Preprocessing. Data . reduction. Sampling. Dimensionality reduction. 严超赣. Chao-Gan Yan, Ph.D.. yancg@psych.ac.cn. http://. rfmri.org. /. yan. Institute of Psychology, Chinese Academy of Sciences. DPARSF. (Yan and Zang, 2010). 2. Data Processing Assistant for Resting-State fMRI (DPARSF). HCP . D. ata. Qunqun. Y. u. . Dr.. . Steve. . Marron. ,. . Dr.. . Kai. . Zhang. . &. . Dr.. . Ben. . Risk. University. . of. . North. . Carolina. . at. . Chapel. . Hill. Human. . What Is Data Mining?. Many people treat data mining as a synonym for another popularly used term, knowledge discovery from data, or KDD, while others view data mining as merely an essential step in the process of knowledge discovery. . Shaleen. Deep. shaleen. @. cs.wisc.edu. Wisconsin DB Affiliates 2021. UNIVERSITY of WISCONSIN-MADISON. INTRODUCTION. Data driven pipelines are the workhorse for modern applications. Workflow for these pipelines consists of several simpler tasks...

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