Methods and principles of building "computer systems that automatically improve with experience."

learn more… | top users | synonyms (1)

0
votes
0answers
3 views

mahout kmeans class not found exception

I have configured Hadoop in Psuedo-Distributed mode. I have succesfully created sequence-files and tf-idf vectors(using seq2sparse) and am trying to run mahout kmeans from command-line as follows: ...
0
votes
0answers
2 views

What techniques infer dependencies between time series?

I'm working on an ML project. We have an app where users can track 1) binary variables and 2) quantities over time on a scale from one to ten. For example, at a given given time they may track whether ...
0
votes
0answers
5 views

VC Dimension of the set of canonical hyperplanes

This is a proof of the theorem about VC Dimension of the set of canonical hyperplanes from Professor Mohri's lecture slide. I'm having difficulty with understanding the inequality$$ \forall i \in ...
0
votes
0answers
10 views

Upcoming areas in theoretical Bayesian Machine Learning

I will soon be going for a postdoc position at a new university. One thing that the panelist asked me to think of is if I were to start, what would I work on. Now the thing is so far with my PhD ...
0
votes
0answers
9 views

Advanced Method in Machine Learning to Learn Objects Position

I have done research about tracking of human body, face, hands, pedestrian etc. Can you point me to the methods in machine learning that learn the changes in position of multiple objects for object ...
0
votes
0answers
3 views

RSNNS neural networks, checking percentage correct.

For those who have some experience with RSNNS, I'm trying to build a neural network for reading aloud, using RSNNS in R. To give some information about what I'm doing and using. I'm using orthographic ...
1
vote
1answer
13 views

Is there a difference between on-line learning, incremental learning and sequential learning?

What I mean is the following: Instead of processing all the training data at once and calculating a model or hypothesis, we process one data point at a time and update the model directly afterwards. ...
0
votes
0answers
6 views

How should I measure difference between user behavior / model performance on different population?

I am developing a recommendation engine whose goal is to suggest data exploration routes to non-technical users. The underlying model is content based, with the training data made up of the behavior ...
0
votes
0answers
10 views

How to use Particle Swarm Optimization for finding optimal bandwidth with cross-validation?

I want to use Particle Swarm Optimization (PSO)for finding optimal smoothing parameters of a kernel density estimation problem. Initially I tried to find the same using grid search method,but the ...
1
vote
0answers
6 views

Touch times to authenticate user

for a project I gathered touch data of different users when they tap a rhythm repeatedly on the touch screen in a game. ...
0
votes
0answers
23 views

how to solve an optimization problem? [on hold]

I am reading an article with title "Learning a distance metric from relative comparisions" lately. http://www.cs.cornell.edu/people/tj/publications/schultz_joachims_03a.pdf. The basic idea for this ...
0
votes
0answers
8 views

Scikit Random forest pred_proba gives rounded off values

I am using random forest in scikit learn for classification and for getting the class probabilities , I used pred_proba function. But strangely it outputs probabilities rounded to first decimal place ...
0
votes
2answers
29 views

Name some techniques similar to Random Forests

I'm interested in what techniques are out there that are similar to, but not the same as, Random Forests. Either for classification or regression or both. Particularly interested in techniques which ...
0
votes
0answers
40 views

Fitting a trading model [on hold]

I have a high frequency time series of the bid and ask prices of a stock recorded on every tick. For each data point I also have a certain indicators that predict the future movement of the price. The ...
1
vote
1answer
36 views

Weight shrinking in linear regression by L2 regularization

Quoting Prof. Bengio from his Deep Learning text (http://www.iro.umontreal.ca/~bengioy/dlbook/regularization.html), $ w = (X^{T}X + \alpha I)^{-1}X^{T}y $ We can see L2 regularization causes ...
0
votes
0answers
5 views

Reduce the FP rate for a Random Forest (sklearn)

I am working with the scikit-learn random forest classifier and I want to reduce the FP rate by increasing the number of trees needed for a successful vote from greater than 50% to say 75%, after ...
0
votes
0answers
7 views

How to model the problem of predicting failure in Server Clusters

The problem goes as follows - There is a cluster of Servers. Whenever there is failure/anomaly in any of the server, a report is logged. Some of the features of the log report are Time of Failure ...
0
votes
0answers
8 views

Website classification using metadata features

I want to fit a model that predicts a website type according to metadata features that I manually collected, such as - Average text length, average # of pics, average outgoing links per page, etc... ...
0
votes
0answers
19 views

Getting an error message “Error in if(reached.threshold < min.reached.threshold)…” while training network using neuralnet package

I'm using R to create train and test a neural network on a time series (the annual sales of a company over a large period of time). As using the package's default learning algorithm (resilient ...
10
votes
3answers
437 views

What can we learn about the human brain from artificial neural networks?

I know my question/title is not very specific, so I will try to clearify it: Artificial neural networks have relatively strict designs. Of course, generally, they are influenced by biology and try to ...
1
vote
1answer
72 views

Why is SVM better for bioinformatics analysis?

I have used five different algorithms: bagging, boosting, C4.5, random forests and SVM, for binary classification of biological data relating to peptide sequence. The dataset comprised of ...
1
vote
2answers
33 views

what is the difference between area under roc and weighted area under roc?

Thanks in advance for the help. I have an unbalanced dataset that I am using for a binary classification problem. The classes are unbalanced. I believe that in such a case that weighted area under ...
1
vote
0answers
13 views

how to understand this neighborhood components analysis model?

I am reading an article with title "neighborhood components analysis" lately. http://papers.nips.cc/paper/2566-neighbourhood-components-analysis.pdf. This article is trying to introduce a linear ...
2
votes
1answer
42 views

How to use linear regression for heavily skewed purchase data?

I am trying to use multiple linear regression to predict the amount that a particular user will spend in a particular time frame on a particular site. Part of the problem is that there are very few ...
1
vote
1answer
37 views

In a Boltzmann machine, why isn't there a simple expression for the optimal edge weights in terms of correlations between variables?

Suppose I have a fully connected, fully visible Boltzmann machine (no hidden variables) with binary variables $x_i\in \{+1, -1\}$ that defines the probability distribution $$ p(\mathbf{x} ; ...
0
votes
0answers
12 views

when to stop this convex optimizations algorithm?

I am reading the article with title "metric learning with collaping classes" lately http://papers.nips.cc/paper/2947-metric-learning-by-collapsing-classes.pdf. See this thread (what is 1/0 in this ...
0
votes
0answers
18 views

Active acquiring as a special case of active learning

I explore an approach for collecting data. This approach is similar to active learning, but there are few differences. The focus of the approach is on collecting training data (labeled data) ...
2
votes
1answer
42 views

train an SVM via back propagation?

I was wondering if it was possible to train an SVM (say a linear one, to make things easy) using back propagation? Currently, I'm at a road block, because I can only think about writing the ...
2
votes
3answers
57 views

Use Edge detection in Image classification

I am having five types of objects (flower, building, face, pair of shoes and a car) in my object recognition and i need to classify these. Identifying through edges in this type of data set seems to ...
9
votes
4answers
873 views

Why is Logistic Regression called a Machine Learning algorithm?

If I understood correctly, in a Machine Learning algorithm, the model has to learn from its experience, i.e when the model gives the wrong prediction for the new cases, it must adapt to the new ...
1
vote
1answer
37 views

What does “node size” refer to in the Random Forest?

I do not understand exactly what is meant by node size. I know what a decision node is, but not what node size is.
3
votes
1answer
47 views

Anomaly detection in time series data

Hi I have a large data set of objects, each containing a list of the same attributes. The data is arranged in a time series so that the value for an attribute for an object is indexed by its time. I ...
3
votes
1answer
15 views

nested cross-validation

if my outer cv is 5-fold, after the process, i have 5 final models, then apply these 5 final models from each CV to the whole dataset (training+validation+testing). For my case, the final 5 accuracy ...
0
votes
1answer
27 views

Using Fisher LDA in R

I have run a large study looking at traumatic brain injury in patients I have conducted CT scans on patients very soon after the injury as well as neurocognitive testing and then repeated this at 1 ...
2
votes
1answer
33 views

Can I Interpret the impact of variables like positive or negative on the model by Random Forest, as I can do by Logistic Regression

I have created a model for prediction of candidates presence or not . I have used Logistic Regression and Random Forest . By Logistic Regression, I got coefficients associated with 100 features and I ...
0
votes
1answer
27 views

Independence of data points assumption

While reading an ML book, I realized that most of the time, the input data points are correlated with each other, and hence their observation is not independent. But then, why do we assume that the ...
1
vote
0answers
13 views

R | NA/NaN/Inf in foreign function call | e1071 SVM [migrated]

Dataset: https://archive.ics.uci.edu/ml/datasets/Chess+%28King-Rook+vs.+King-Pawn%29 Code: ...
0
votes
0answers
18 views

Conclusion from PCA of dataset

I have a set of data for sequence labeling. I did PCA with (with 2 principal components on the x and y axis) on the dataset and it turns out as below: Using an LSTM network to classify the dataset ...
2
votes
0answers
37 views

How are radial basis functions (RBFs) networks extended to use multiple layers?

I am trying to understand the interpretation of radial basis functions (RBFs) as networks and then trying to understand the relationship it has to "normal" neural networks and how to extend them to ...
3
votes
2answers
111 views

Can a neural network learn a functional, and its functional derivative?

I understand that neural networks (NNs) can be considered universal approximators to both functions and their derivatives, under certain assumptions (on both the network and the function to ...
2
votes
1answer
47 views

What is the right algorithm to detect segmentations of a line chart?

To be concrete, given 2D numerical data as is shown as line plots below. There are peaks on a background average movement (with small vibrations). We want to find the values of pairs (x1, x2) if those ...
2
votes
0answers
32 views

How is prior knowledge of letter/word patterns incorporated into handwriting (or speech) recognition?

Using handwriting recognition as an example, we can train various models to recognise individual characters but to actually be useful we must incorporate prior knowledge of common character sequences, ...
2
votes
0answers
55 views

what is 1/0 in this article?

I am reading the article with title "metric learning by collapsing classes" lately http://papers.nips.cc/paper/2947-metric-learning-by-collapsing-classes.pdf . Everything goes well until the equation ...
2
votes
1answer
35 views

How does one do Stochastic Gradient Descent (SGD) on an objective function that has a regularizer?

I know that for Stochastic Gradient Descent, one picks a data point $(x_n, y_n)$ at random from the training set $S_N$ and then updates the parameter of the model in question. If the cost function ...
0
votes
0answers
7 views

Bigdata cluster compatible distributed predictive model [migrated]

I might be asking a dumb question but my question is can I write a python program (lets say a classifier) using some library that scales in hadoop (not only using a simple parallel processing).The ...
2
votes
1answer
75 views

What algorithm can I use to find correlations between events?

I am new to machine learning so I am trying to find some literature but I'm not even sure what to Google for. My data is of the following form: ...
3
votes
1answer
28 views

sampling distribution of the mean for arbitrary 1-D pdf

I want to compute the sampling distribution of the mean for $k$ samples from an arbitrary, known probability density $f(x)$, with $x \in \mathbb{R}$. What is the most efficient way to do so ...
0
votes
1answer
27 views

what is the relation between “data visualization” and “embedding”? [closed]

I am reading several articles about metric learning lately. Sentences like "build better data visualizations via embedding" and "low-dimensional linear embedding of labeled data" pop up very oftenly. ...
0
votes
0answers
18 views

Feature selection + classification in Caret

I'm using Caret to apply a bunch of different machine learning algorithms for phenotype prediction from gene expression data. With about 20,000 genes, I'd like to perform filter feature selection ...
0
votes
0answers
13 views

How to obtain Matthews correlation coefficient in Rocr? [closed]

I am trying the following example: ...