MLC - Revision history

MatteoMatteucci at 17:16, 26 January 2009

2009-01-26T17:16:37Z

MatteoMatteucci at 17:16, 26 January 2009

2009-01-26T17:16:11Z

MatteoMatteucci at 17:15, 26 January 2009

2009-01-26T17:15:37Z

MatteoMatteucci at 17:11, 26 January 2009

2009-01-26T17:11:52Z

MatteoMatteucci at 17:06, 26 January 2009

2009-01-26T17:06:06Z

MatteoMatteucci at 17:05, 26 January 2009

2009-01-26T17:05:24Z

MatteoMatteucci: /* Supervised */

2009-01-26T17:04:22Z

‎Supervised

AhmedGhozia at 08:56, 26 January 2009

2009-01-26T08:56:27Z

AhmedGhozia at 08:56, 26 January 2009

2009-01-26T08:56:00Z

SimoneTognetti: New page: ==== Supervised ==== ---- * + Machine learning introduction, paradigm, estimation ... [Matt] ======Distributions of data====== * + Feature selection and projection (PCA, LDA, ICA, ...) [...

2009-01-25T18:08:24Z

New page: ==== Supervised ==== ---- * + Machine learning introduction, paradigm, estimation ... [Matt] ======Distributions of data====== * + Feature selection and projection (PCA, LDA, ICA, ...) [...

New page

==== Supervised ====
----

* + Machine learning introduction, paradigm, estimation ... [Matt]

======Distributions of data======
* + Feature selection and projection (PCA, LDA, ICA, ...) [Rossella (?)+ Simone]

====== Linear & other ======
* - Good old stuff: logistic regression, linear regression [Bernardo (?)]
* + LDA

====== Rules======
* + Decision trees [Matt]
* ~ Decision rules [Matt + Andrea (?)]
* - Association rules [?]

====== Bayes ======
* + Bayesian classifiers [Matt]

====== Non parametric methods ======
* - KNN & friends, Locally weighted regression,

====== ...? ======
~ SVM and Kernel methods [Matt (?) + Luigi (?) + (?)]

==== Statistical Learning & Unsupervised ====
----

====== Graphical models ======

* + Markov Chains [Matt + Bernardo (?) +Simone]
* ~ Bayesian networks [Matt + Luigi (?)]
* (Dynamic Bayesian Networks) + Hidden Markov Models [Matt + Simone (?)]

====== Expectation & maximization ======
* Kernel based density estimation, ... [Rossella (?) + Luigi (?) + Simone]
* Clustering

==== Knowledge representation ====
----

* - ontologies ...

==== Text analisys ====
----

*- text analysis, classification, relevance feedback, latent semantic

==== Image analisys ====

==== Unmapped:====
* - Adaboost, boosting and bagging ... [?]
* ~ Cross-Validation, Bootstrapping, and model evaluation [Matt (?)]

* + Clustering galore [Davide (?)]
indexing, ...

@@ Line 51: / Line 51: @@
 ==== Knowledge representation and Learning ====
 ----
 * - ontologies ...
 ==== Text analysis and learning ====
 ----
 * - text analysis, classification, relevance feedback, latent semantic [Ahmed]
 ==== Image analysis and learning ====
 ----
 * - Image analysis and learning

@@ Line 51: / Line 51: @@
 ==== Knowledge representation and Learning ====
 ----
 * - ontologies ...
 ==== Text analysis and learning ====
 ----
 * - text analysis, classification, relevance feedback, latent semantic [Ahmed]
 ==== Image analysis and learning ====
 * - Image analysis and learning

@@ Line 4: / Line 4: @@
 * + Machine learning introduction, paradigm, estimation ... [Matt]
-==== Supervised ====
+==== Supervised Learning ====
 ----
@@ Line 23: / Line 23: @@
 ====== Kernel methods ======
-~ SVM and Kernel methods [Matt (?) + Luigi (?) + (?)]
+* ~ SVM and Kernel methods [Matt (?) + Luigi (?) + (?)]
-==== Unsupervised ====
+==== Unsupervised Learning====
 ----
 ======Distributions of data======
 * + Feature selection and projection (PCA, ICA, ...) [Rossella (?)+ Simone]
-* Kernel based density estimation, ... [Rossella (?) + Luigi (?) + Simone]
-* Clustering
+======Clustering======
 ====== Graphical models ======
 * ~ Bayesian networks  [Matt + Luigi (?)]
-======Time Varing Models======
+======Non Parametric techniques======
 * + Markov Chains [Matt + Bernardo (?) +Simone]
 * + Hidden Markov Models [Matt + Simone (?)]
@@ Line 42: / Line 46: @@
 ==== Learning Techniques and Methodologies ====
 ----
+* ~ Cross-Validation, Bootstrapping, and model evaluation [Matt (?)]
-==== Knowledge representation ====
+==== Knowledge representation and Learning ====
 ----
 * - ontologies ...
-==== Text analysis ====
+==== Text analysis and learning ====
 ----
-*- text analysis, classification, relevance feedback, latent semantic [Ahmed]
+* - text analysis, classification, relevance feedback, latent semantic [Ahmed]
-==== Image analysis ====
+==== Image analysis and learning ====
+* - Image analysis and learning
-−
-==== Unmapped:====
-* - Adaboost, boosting and bagging ... [?]
-* ~ Cross-Validation, Bootstrapping, and model evaluation [Matt (?)]
-−
-* + Clustering galore [Davide (?)]
-indexing, ...

← Older revision		Revision as of 17:06, 26 January 2009
Line 1:		Line 1:
−	==== MLC: Machine Learning Curse ====	+	==== Introduction to the MLC a.k.a. the Machine Learning Curse ====
	----		----

← Older revision		Revision as of 17:05, 26 January 2009
Line 1:		Line 1:
−	MLC: Machine Learning Curse ~~(pun intended!)~~	+	==== MLC: Machine Learning Curse ====
		+	----

	* + Machine learning introduction, paradigm, estimation ... [Matt]		* + Machine learning introduction, paradigm, estimation ... [Matt]

@@ Line 7: / Line 7: @@
 ----
-======Distributions of data======
+====== Good old stuf from machine learning======
-* + Feature selection and projection (PCA, LDA, ICA, ...) [Rossella (?)+ Simone]
-−
-====== Linear & other ======
-* - Good old stuff: logistic regression, linear regression [Bernardo (?)]
-* + LDA
-−
-====== Rules======
 * + Decision trees [Matt]
 * ~ Decision rules [Matt + Andrea (?)]
 * - Association rules [?]
-====== Bayes ======
+====== Statistical approaches ======
 * + Bayesian classifiers [Matt]
@@ Line 26: / Line 22: @@
 * - KNN & friends, Locally weighted regression,
-====== ...? ======
+====== Kernel methods ======
 ~ SVM and Kernel methods [Matt (?) + Luigi (?) + (?)]
-==== Statistical Learning & Unsupervised ====
+==== Unsupervised ====
 ----
 ====== Graphical models ======
 * + Markov Chains [Matt + Bernardo (?) +Simone]
-* ~ Bayesian networks  [Matt + Luigi (?)]
+* + Hidden Markov Models [Matt + Simone (?)]
-* (Dynamic Bayesian Networks)  + Hidden Markov Models [Matt + Simone (?)]
+* - Dynamic Bayesian Networks
 ==== Knowledge representation ====