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1
Intro
2
Big Data
3
Size vs. Complexity
4
Mathematical Modeling
5
What Do Models Buy You?
6
Hierarchical Clustering
7
Problems with Algebraic Modeling
8
Problems with Clustering
9
The Shape of Data
10
How to Build Networks for Data Sets
11
Topological Modeling
12
Unsupervised Analysis - Diabetes
13
Unsupervised Analysis/ Hypothesis Generation
14
Microarray Analysis of Breast Cancer
15
Different Platforms for Microarrays
16
TDA and Clustering
17
Feature Modeling
18
Explaining the Different cohorts
19
UCSD Microbiome
20
Pancreatic Cancer
21
Hot Spot Analysis and Supervised Analysis
22
Model Diae
23
Create network of mortgages
24
Surface sub-populations
25
Improve existing models
26
Serendipity
27
Exploratory Data Analysis
Description:
Explore topological modeling of complex data in this 55-minute AMS-MAA Invited Address from the 2018 Joint Mathematics Meetings. Delve into the challenges of big data analysis, comparing size versus complexity and examining traditional mathematical modeling approaches. Discover the limitations of algebraic modeling and clustering techniques before exploring the concept of data shape. Learn how to construct networks for data sets and apply topological modeling to various real-world scenarios, including diabetes analysis, breast cancer microarray studies, and microbiome research. Investigate feature modeling, hot spot analysis, and supervised analysis techniques. Gain insights into improving existing models, surface sub-populations in mortgage data, and leverage serendipity in exploratory data analysis.

Topological Modeling of Complex Data

Joint Mathematics Meetings
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