Subscribe to Vincent Granville's Weekly Digest:
Cristian Mesiano
  • Male
  • zürich
  • Switzerland
Share Twitter

Cristian Mesiano's Friends

  • Marco Santambrogio
  • Rosaria Silipo
  • Amy

Cristian Mesiano's Groups

Cristian Mesiano's Discussions

Classification Step: C 5.0 vs SVM
2 Replies

A new post on my blog:An early approach at "document classifier".I hope it will triggers some discussion on classification techniques.…Continue

Tags: SVM, C5, Classification

Started this discussion. Last reply by Cristian Mesiano Sep 12, 2011.

 

Cristian Mesiano's Page

Latest Activity

Cristian Mesiano posted a blog post

Document Clustering and Graph Clustering: graph entropy as linkage function

Let's continue our discussion about the applications of the graph entropy concept.Today I'm going to show how we can re-use the same concept on the document clustering.What I want to highlight is that through such methodology it's possible to:extract from a document the relevant words (as discussed here);clustering of the words of a document (as…See More
Nov 17, 2012
0 Comments
Cristian Mesiano posted a blog post

Key words through graph entropy Hierarchical clustering

CLICK HERE TO READ MOREIn the last post I showed how to extract key words from a text through a principle called graph entropy.Today I'm going to show another application of the graph entropy in order to extract clusters of key words.WhyThe key words of a document depict the main topic of the content, but if the document is big, often, there are many different sub topics related to the main.In this perspective, a clusters of…See More
Oct 24, 2012
0 Comments
Cristian Mesiano posted a blog post

Graph Entropy to extract relevant words

I would share with you some early results about a research I'm doing in the field of "graph entropy" applied to text mining problem.click here to read the entire postWhy Graph Entropy is so important?Based on the main concept of entropy the following assumptions are true:The entropy of a graph should be a functional of the stability of the structure (so that it depicts in some…See More
Sep 24, 2012
0 Comments
Cristian Mesiano posted a blog post

Function minimization: Simulated Annealing led by variance criteria vs Nelder Mead

Most of the datamining problems can be reduced as a minimization/maximization problem.... click here to read the entire postExamplesLet's consider  easy scenarios where the function cost is conditionated just by two parameters.…See More
Aug 12, 2012
0 Comments
Cristian Mesiano posted a blog post

Simulated Annealing: How to boost performance through Matrix Cost rescaling

One of the most widely algorithm used in Machine Learning is the Simulated Annealing (SA).The reason of its celebrity lays in:Simplicity of implementationbroad spectrum of applicability ... click here to read the entire postThe experimentsI considered two instances of the problem, the first one with 10 towns and the second one with 50 towns.Even if for this kind of problem there are…See More
Jul 3, 2012
0 Comments
Cristian Mesiano posted a blog post

Outlier analysis: Chebyschev criteria vs approach based on Mutual Information

As often happens, I usually do many thing in the same time, so during a break while I was working for a new post on applications of mutual information in data mining, I read the interesting paper suggested by Sandro Saitta on his blog (dataminingblog)  related to the outlier detection. ...Usually such behavior is not proficient to obtain good results, but this time I think that the change of prospective has been positive!…See More
May 23, 2012
0 Comments
Cristian Mesiano posted a blog post

Uncertainty coefficients for Features Reduction - comparison with LDA technique

...click here to read the entire post...Uncertainty coefficientConsider a set of people's data labelled with two different labels, let's say blue and red, and let's assume that for this people we have a bunch of variables to describe them.Moreover, let's assume that one of the variables is the social security number (SSN) or whatever univocal ID for each person.Let me do some…See More
May 5, 2012
0 Comments
Cristian Mesiano posted a blog post

Earthquake prediction through sunspots part II: common Data mining mistakes!

While I was writing the last post I was wondering how long before my followers notice the mistakes I introduced in the experiments.Let's start the treasure hunt!1. Don't always trust your data: often they are not homogeneous....click here to read the entire postA good data miner must always check his dataset! you should always ask to yourself whether the data have been produced in a congruent way.…See More
Apr 4, 2012
0 Comments
Cristian Mesiano posted a blog post

Support Vector Regression (SVR): predict earthquakes through sunspots

In the last months we discussed a lot about text mining algorithms, I would like for a while focus on data mining aspects.Today I would talk about one of the most intriguing topics related to data mining tasks: the regression  analysis....To read the entire post click hereExperiment: Earthquakes prediction using sunspots as regressorEarly warning: this is just a tutorial, so…See More
Mar 7, 2012
0 Comments
Cristian Mesiano posted a blog post

Features Extraction: Co-occurrences and Graph clustering

In the last two post we have discussed about co - occurrences analysis to extract features  in order to classify documents and extract "meta concepts" from the corpus.We have also noticed that this approach doesn't return better than the traditional bag of words.I would now explore some derivation of this approach, taking advantage of the graph theory.the graph of the co occurrences is really huge and complex, how could we reduce its complexity without big information loss?The Kcore…See More
Feb 29, 2012
0 Comments
Cristian Mesiano posted a blog post

Document Classification: latent semantic vs bag of words. Who is the best?

We have seen few posts ago an approach to extract meta "concepts" from text based on latent semantic paradigm.In this post we apply this approach to classify documents, and we do a comparison between this approach and the canonical bag of words.The comparison test will be done through the ensemble method already showed in the last post.To read the entire post click here.The…See More
Feb 20, 2012
0 Comments
Cristian Mesiano's blog post was featured

Document Classification: how to boost your classifier

ADaBoost.M1 tries to improve step by step the accuracy of the classifier analyzing its behavior on training set. (Of course you cannot try to improve the classifier working with the test set!!).Here lays the problem, because if we choose as "weak algorithm" an SVM, we know that almost always it returns excellent accuracy on the training set with results closed to 100% (in term of true positive).In this scenario, try to improve the accuracy of classifier assigning different weights to the…See More
Jan 30, 2012
0 Comments
Cristian Mesiano posted a blog post

Document Classification: how to boost your classifier

ADaBoost.M1 tries to improve step by step the accuracy of the classifier analyzing its behavior on training set. (Of course you cannot try to improve the classifier working with the test set!!).Here lays the problem, because if we choose as "weak algorithm" an SVM, we know that almost always it returns excellent accuracy on the training set with results closed to 100% (in term of true positive).In this scenario, try to improve the accuracy of classifier assigning different weights to the…See More
Jan 30, 2012
0 Comments
Cristian Mesiano posted a blog post

Extract meta concepts through co-occurrences analysis and graph theory

....So what I did is the following (be aware that is not the formal implementation of LSA!):Filter and take the base form of the words as usual.Build the multidimensional sparse matrix of the co-occurrences;I calculated for each instance the frequency to find it in the corpus;I calculated for each instance the frequency to find it in the doc;I weighted such TF-IDF considering also the distance among the co-occurrences.In this way we are able to rank all co-occurrences and set a threshold to…See More
Jan 13, 2012
0 Comments
Cristian Mesiano posted a blog post

Clustering algorithm to approximate functions

The strategy is very easy to describe: 1. Divide the domain of your function in k sub intervals. 2. Initialize k monomials; 3. Consider the monomials as centroids of your clustering algorithm. 4. Assign the points of the function to each monomial in compliance to the cluster algo. 5. Use the gradient descent to adjust the parameters of each monomial. 6. Go to 4. until the accuracy is good enough.Read the entire post at:…See More
Dec 15, 2011
0 Comments
Cristian Mesiano posted a blog post

Power Real Polynomial to approximate functions: The Gradient Method

In the real world rarely a problem can be solved using just a single algorithm, more often a solution is a chain of algorithms where the output of the former is the input for the follower.But you know that quite often machine learning algorithms return functions almost always extremely complex, and they don’t fit directly in the next step of your strategy.In these conditions, it is really helpful the trick of the function approximation, that is, we reduce the complexity of our original model…See More
Dec 8, 2011
0 Comments

Profile Information

Short Bio:
I am graduated (Master Degree) in CS and I work in a Enterprise Content Management department in a multinational company (Reinsurance focused). Our tasks are focused on document auto classification, document data extraction, selective search. We mix latest algorithms with Business requirements to offer real solution for demanding content consumers!
My Website or LinkedIn Profile (URL):
http://textanddatamining.blogspot.com/
Field of Expertise:
Business Analytics, Predictive Modeling, Data Mining, Econometrics, Statistical Programming, Artificial Intelligence
Years of Experience in Analytical Role:
8
Professional Status:
Other
Interests:
Networking
What is your Favorite Data Mining or Analytical Website?
http://textanddatamining.blogspot.com/
Your Company:
Swiss RE

Cristian Mesiano's Blog

Document Clustering and Graph Clustering: graph entropy as linkage function

Let's continue our discussion about the applications of the graph entropy concept.

Today I'm going to show how we can re-use the same concept on the document clustering.

What I want to highlight is that through such methodology it's possible to:



  1. extract from a document the relevant words (as discussed …
Continue

Posted on November 17, 2012 at 1:35am

Key words through graph entropy Hierarchical clustering

CLICK HERE TO READ MORE

In the last post I showed how to extract key words from a text through a principle called graph entropy.

Today I'm going to show another application of the graph entropy in order to extract clusters of key words.

Why

The key words of a document depict the main topic of the content, but if the document is big, often, there are many different sub topics related to the…

Continue

Posted on October 24, 2012 at 11:34am

Graph Entropy to extract relevant words

I would share with you some early results about a research I'm doing in the field of "graph entropy" applied to text mining problem.

click here to read the entire post

Why Graph Entropy is so important?

Based on the main concept of entropy the following assumptions are true:



  • The entropy of a graph should be a functional of the…
Continue

Posted on September 24, 2012 at 2:39pm

Function minimization: Simulated Annealing led by variance criteria vs Nelder Mead

Most of the datamining problems can be reduced as a minimization/maximization problem.

... click here to read the entire post

Examples
Let's consider  easy scenarios where the function cost is conditionated just by two parameters.…

Continue

Posted on August 12, 2012 at 3:09am

Comment Wall (1 comment)

You need to be a member of AnalyticBridge to add comments!

Join AnalyticBridge

At 1:23pm on August 31, 2011, Marco Santambrogio said…

Ciao Cristian.

Bhe consigli su questo tema sono sempre delicati.

Sul text mining ti direi di seguire bene gli sviluppi di SAS e di EXPERT SYSTEM

In generale, gli Analytics un pò alla volta si stanno sviluppando, non solo nel Finance e Telco.

  

 
 
 

Top Content 

1 How to develop churn prediction model for telecom company?

How to develop churn prediction model for telecom company?
2 Map of Data Science University Programs

Map of Data Science University Programs
3 Use PRESS, not R squared to judge predictive power of regression

Use PRESS, not R squared to judge predictive power of regression
4 Text mining: alternative to Wordflex?

Text mining: alternative to Wordflex?
5 Audience expansion

Audience expansion
6 Simple solutions to make videos with R

Simple solutions to make videos with R
7 The End of Theory: The Data Deluge Makes the Scientific Method Obsolete | Wired

The End of Theory: The Data Deluge Makes the Scientific Method Obsolete | Wired
8 Is Open Source Really Free?

Is Open Source Really Free?
9 Understanding the Kalman Filter Application in Economic Time Series Data

Understanding the Kalman Filter Application in Economic Time Series Data
10 Identifying the number of clusters: finally a solution

Identifying the number of clusters: finally a solution

Follow us

Big Data Jobs

Data Scientist - Amazon

Business Analyst - Amazon

Senior Statistician, Marketing Analytics

Fraud Data Analyst

Data Scientist - Apple

Data Mining Scientist - Apple

Data Scientist

Analytics Consultant

Marketing Analyst - Mobile (Zappos.com)

Director, Network Data Science

© 2013   AnalyticBridge.com is a subsidiary and dedicated channel of Data Science Central LLC

Badges  |  Report an Issue  |  Terms of Service