Methods and principles of building "computer systems that automatically improve with experience."
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0answers
16 views
May I put few questions on MaxEnt?
I was having few questions on MaxEnt.
a) Is MaxEnt and Maximum Entropy Markov Model same or different?
b) Does MaxEnt has any hidden layer?
c) How may we estimate the model in MaxEnt?
If any of ...
0
votes
0answers
79 views
Computing overhead of statistical models for training?
Could someone provide overhead of the following model for training (With respect to input size or if there are any relevant parameters). Overhead I mean somewhat like asymptotic time complexity form.
...
0
votes
2answers
74 views
Normalizing SVM predications to [0,1]
I have trained an linear SVM which takes a pair of objects, computes features and is expected to learn a semantic similarity function between objects(we can say that it predicts whether the two ...
1
vote
1answer
65 views
When to Log/Exp your Variables when performing Linear Regression?
I'm doing regression using Random Forests for predicting prices based on several attributes. Code is written in Python using Scikit-learn.
How do you decide whether you should transform your ...
1
vote
1answer
35 views
The weight updating in adaboost
1.AdaBoost updates the weight of the sample By the current weak classifier in training each stage. Why doesn't it use the all of the previous weak classifiers to update the weight. (I had tested it ...
2
votes
2answers
70 views
Is it essential to do normalization for SVM and Random Forest?
My features' every dimension has different range of value. I want to know if it is essential to normalize this dataset. Thanks
3
votes
1answer
41 views
prequential evaluation - classification
I perform prequential evaluation like this: start with a training set, classify a number of examples, then add the correctly classified examples in the training set and continue to classifying the ...
5
votes
2answers
257 views
What is the difference between a neural network and a deep belief network?
I am getting the impression that when people are referring to a 'deep belief' network that this is basically a neural network but very large. Is this correct or does a deep belief network also imply ...
0
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0answers
25 views
PLA vs Regression
Just started getting into machine-learning, and I'm wondering if there is a relationship between the Perceptron learning algorithm and linear regression?
0
votes
1answer
154 views
Error metric for a regression model with two dependent variables
I'm working on an algorithm that estimates two parameters of its input data. I have a representative set of samples with the true parameters, to act as a ground truth. As this algorithm uses a ...
1
vote
1answer
165 views
Observation symbols for training a set of HMMs
If we are to classify 2 separate classes/actions using HMMs, we design 2 separate HMMs (one for each class). Do they share same set or a different set of observations-symbols for each of the HMM?
If ...
0
votes
2answers
85 views
Drawing inferences from word counts
I'm trying to figure out if there is a good model that can connect word counts to classifying whether or not a person might go to an event. Here's the description: I have users, and events. 100 ...
0
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0answers
26 views
Scikit-learn reports memory error when fitting Gaussian process model
I want to fit a Gaussian Process with about 50,000 training examples and 130 features using Scikit-learn. Right now, I only have 1 theta hyperparameters as I run the process with all defaults. But I ...
8
votes
5answers
2k views
Large scale text classification
I am looking to do classification on my text data. I have 300 classes, 200 training documents per class (so ...
4
votes
1answer
154 views
Incorporating a treatment into a classification scheme
I have about 400 pieces of silver of different geometric dimensions. They were assigned to six groups and each group went through a series of stress tests, such as bending, pulling, putting in fire ...
3
votes
2answers
218 views
How to compute the partial derivative of the cost function of mean regularized multi task learning?
Background: This is the costfunction of Mean Regularized Multi Task Learning.
This is a typical linear regression learning model, with the only difference being that there's multiple instances of ...
1
vote
1answer
30 views
Categorical value “stuck” during sampling of my model
I'm having some troubles with the implementation in pyMC of my probabilistic model.
Note: you can skip directly to the code section, if you're not interested on the use of the model.
The model ...
2
votes
2answers
67 views
Why can the margin of SVM be approximated by 1?
The separate function of SVM is :
$wx+b=0$
The function distance of support vector to the separate plane is :
$|r| = wx_i+b$
And we can normalize the $w$, then the distance can be write as :
...
0
votes
0answers
17 views
Estimating sparse inverse covariance matrix in high dimensional data
I am trying to estimate the graph in very high dimensional data, I mean with million nodes. Up to now all the papers that I have found, they are limited to few thousands.
All of them like graphical ...
0
votes
2answers
30 views
clustering gene expression data
I have a question about clustering.
I' m managing gene expression microarray data and I would like to cluster them in classes.
I searched around to find the best clustering algorithm for my data, ...
4
votes
1answer
170 views
Can a model of P(Y|X) be trained via stochastic gradient descent from non-i.i.d. samples of P(X) and i.i.d. samples of P(Y|X)?
When training a parameterized model (e.g. to maximize likelihood) via stochastic gradient descent on some data set, it is commonly assumed that the training samples are drawn i.i.d. from the training ...
-1
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0answers
68 views
Is it fair to say that time-series violates IID? [closed]
First a little background.
It is said that, for the supervised learning framework. there should be a probability distribution over the input space, $P$ over $X$, (for example, as stated here ...
1
vote
1answer
130 views
How to combine the responses of two sensors?
I have two sets of responses from two different sensors. In each set, the first column is distance measured in feet, and the second column is the response of the sensor. Sensor A has response values ...
0
votes
0answers
18 views
Adaboost with a basic linear classifier
I am trying to implement the adaboost algorithm with the simple linear classifier as weak learner. For this I am using the pseudo inverse rule. i.e. w = inv(X*X')*X*t, where w is the weight vector of ...
0
votes
1answer
138 views
How to calculate recall-precision curves
I am trying to plot a recall-precision curve for an object detection algorithm. In order to detect objects, I create a vote-map (2D histogram) in which object centres are voted for.
I then filter ...
2
votes
1answer
102 views
Representation within a RKHS framework
Given a p.s.d kernel $Q$, can minimization/maximization of $Tr(X^TQX)$ over X be represented within a reproducing kernel Hilbert space (RKHS) framework? If there is a primary concern with the trace ...
4
votes
3answers
113 views
Should you ever standardise binary variables?
I have a data set with a set of features. Some of them are binary (1=active or fired, 0= inactive or dormant) and the rest are real valued, i.e. 4564.342.
I want to feed this data to a machine ...
2
votes
1answer
145 views
Predicting Football match winners based only on previous data of same match
I'm a huge football(soccer) fan and interested in Machine Learning too. As a project for my ML course I'm trying to build a model that would predict the chance of winning for the home team, given the ...
2
votes
2answers
65 views
Can machine learning methods be somehow helpful in solving differential equations?
I noted that regression task in machine learning is somehow related to solving differential equations approximately - both are trying to approximate unknown function.
Then, my question is: Can ML be ...
4
votes
2answers
122 views
When there are many more failures than successes should I let classes be equal in SVM?
I have about 5544 runs where I am trying to classify it as failure or success. Here the number of runs that lead to failure is only 64 and rest is sucess. In that case when I try to use SVM should I ...
1
vote
1answer
68 views
Are there any simple techniques to remove/detect fluctuations during training in matlab plot?
Image below is a Matlab plot from 3-layer perceptron learning with 2 hidden nodes in both hidden layers. Are there simple technique or simple coding to remove or detect these fluctuations during ...
0
votes
1answer
60 views
Minimize a function with respect to a matrix
I have two sets of vectors, A and B. Vectors from set A live in an m-dimensional space, ...
2
votes
0answers
71 views
Universal Approximation Theorem — Neural Networks
I have posted this question elsewhere--MSE-Meta, MSE, TCS, MetaOptimize. Previously, no one had given a solution. But now, here is a really excellent and comprehensive answer.
Universal approximation ...
1
vote
1answer
319 views
Decision boundaries and Gaussian density functions
This is for my hw, and if anyone can solve the first part of the question it will be great.
Here is the question:
Assume a two-class problem with equal a priori class probabilities and Gaussian ...
2
votes
2answers
78 views
What machine learning techniques can, once trained, generate prediction despite some missing inputs?
I have a training set where the inputs & outputs are all present, but I suspect that in the data where I want to do prediction, I will occasionally encounter scenarios where a small fraction of ...
1
vote
2answers
60 views
How to measure weight similarity?
I'm doing some machine learning and get a set of optimum weights in the end. I'd like to verify that these weights are by and large the same no matter how many times I train on the data. I assume that ...
3
votes
1answer
81 views
Which performance measure for unbalanced binary classification without an 'active' class?
My datasets have two classes A and B. The classes should be treated equally (there is no "active/inactive"). The datasets are unbalanced, sometimes A is more frequent, sometimes B is more frequent. ...
0
votes
1answer
47 views
How to adjust machine learning training data set with time
I'm using machine learning to do text classification right now, I first use a training data to train my classifier, then use this classifier to classify text document into different classes. With the ...
2
votes
1answer
91 views
Next steps after “Bayesian Reasoning and Machine Learning”
I'm currently going through "Bayesian Reasoning and Machine Learning" by David Barber and it is an extremely well written and engaging book for learning the fundamentals. So a question to someone who ...
1
vote
1answer
52 views
Online logistic regression?
Here is my problem: I am developing an embedded system for some classification task. I am using Logistic Regression as my classifier. Now I train my classifier, and download my model on to my machine. ...
0
votes
0answers
21 views
time complexity and space complexity for HMM forward recursion
When Reading the HMM models, I found the following discussion on the time complexity and space complexity regarding forward recursion.
I am sort of confusing on the reason of getting O(K^2N) and ...
1
vote
1answer
183 views
LDA projection for classification
I am dealing with 2 class LDA classification problem.
During a test phase (after training), I'm trying to project a feature vector to lower dimensional space.
How do we get the projected test ...
1
vote
1answer
75 views
First steps learning to predict financial timeseries using machine learning
I am trying to get a grasp on how to use machine learning to predict financial timeseries 1 or more steps into the future.
I have a financial timeseries with some descriptive data and I would like to ...
4
votes
1answer
129 views
Confusion related to semisupervised learning in random walk
I am trying to understand the semi supervised learning in random walk. Lets say I have 10 classes and I have some labelled and unlabelled points. Now, I need to find the labels for the unlabelled ...
0
votes
1answer
83 views
How to handle Regression data thats not linear
I'm new to stats and am using Python 2.7 to fit a regression model (Random Forest). When I plot the percentile plot of the prices before and after a log ...
0
votes
0answers
36 views
Appropriate method for supervised learning of small data set with few variables
What method exc. for regression can be used in order to get y=f(x1,x2) on a training set of 800 to 2000 samples? y is a whole number <0,15>, x1,x2 are real <0,40>?
I'm interested in prediction ...
5
votes
1answer
1k views
cforest and randomForest classification prediction error
I used cforest and randomForest for a 300 rows and 9 columns dataset and received good (almost overfitted - error equal to zero) results for randomForest and big prediction errors for cforest ...
0
votes
0answers
21 views
Strategy for building best fit multiple regression model with time lagged variables
I am building a multiple regression model - wrapped in a function - with one dependent variable and a dozen independent variables. The reason why I am building a function is that I need to do this ...
1
vote
0answers
24 views
Find exceptional parameters
I have been given an excel document with many rows full of numbers, some rows are marked.
Each row represents a case in the clinic, each column represents a research test parameter.
I need to find, ...
1
vote
1answer
30 views
Features selection using F-score for multiclass classification
I'm going to implement a feature selection algorithm, and I plan to use the F-score for because of its simplicity. The problem is that, the F-score is used for binary classification. How can it be ...
