Machine learning, a branch of artificial intelligence, is the science of getting computer systems to meaningfully act without being explicitly programmed by human.

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21 views

ice (sleet, glaze ice) [on hold]

Tell me how you can well predict the ice (sleet, glaze ice)? I have a database for a long period of time with different parameters to weather conditions. The first thing that comes to mind - Least ...
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1answer
23 views

Neural Network - single layer perceptron for multiple classes

For activation function in neural network, I have used the function $$\frac{1}{2}(\sin x +1) \enspace .$$ But this will give me the value of either 1 or 0, allowing me to classify only 2 classes. ...
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3answers
38 views

Algorithm: Extracting motion frequency from video

I was wondering if anyone knows of any algorithms or projects that can detect the frequency of a motion from a video clip. Like if I had a video of a bouncing ball with constant frequency, could an ...
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0answers
26 views

Determine function parameters with neural network

I am currently studying a doctoral thesis in control theory. At the end of every chapter there is a simulation of a relative-with-the-subject problem. I have finished the theory,but for further ...
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22 views

Conceptual questions on Hopfield network and Particle Swarm

In continuation to http://stackoverflow.com/questions/22768493/neuralnetwork-activation-function/22918658?noredirect=1#22918658. I am using Hopfield network to recognize 3 characters = 0,1,2. I am ...
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29 views

Measuring standard deviation of patterns

Sometimes in pattern recognition say Character recognition, Hamming distance is used although there are other distance measures. But if the pattern is represented in (1,0,-1) then Hamming distance is ...
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1answer
585 views

How to detect smiles using OpenCV and IntraFace?

I have installed OpenCV and IntraFace, now the code can detect landmarks on the face, like this : Now how can I convert this to a smile detector? I have the landmark points as an array, so I ...
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2answers
50 views

Neural Networks: what's the point of learning features that don't linearly separate?

Unless I'm mistaken, deep neural networks are good for learning functions that are nonlinear in the input. In such cases, the input set is linearly inseparable, so the optimisation problem that ...
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1answer
51 views

SVM Math Question

I'm studying support vector machines and came across this paper. The following equation doesn't make sense to me, especially the part with the 0 ∀i. Any help understanding the basics of SVMs? yi * ...
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1answer
107 views

How could I implement this neural network in R? [closed]

In Establishing, versus maintaining, brain function: a neurocomputational model of cortical reorganisation after injury to the immature brain, Varier et al develop a neural network model of motor ...
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1answer
92 views

A Filter is Sum normalized to 0 and square normalized to 1

Firstly, About the Hierarchical Model And X (HMAX model), i still don't understand what is the difference between the "Original model" and "Standard model". Does in Standard, we use imfilter not conv2 ...
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1answer
127 views

Support Vector Machines as Neural Nets?

This is more of a conceptual question. I have learned about Neural Nets, and I have some clue as to how Support Vector Machines work. I read somewhere however that given the appropriate kernel (is ...
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55 views

In training NN (MLP) based regressions, does local oversampling lead to biases?

I'm using an artificial neural network (ANN) to train a regression analysis. More specifically, I use a simple 3-layer multi-layer perceptron (MLP) with 5–10 input nodes, 10 nodes in the hidden ...
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0answers
263 views

What is average pooling

I was reading an article where they have a set of pages. For every page they extract a feature vector of dimention 300. Then they fuse these vectors into one vector by using a method called average ...
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2answers
76 views

Books/Resources on Sparse Optimization?

I'm looking to learn more about Sparse Optimization and apply it to machine learning problems. Could you please recommend some books/resources on this topic? Both theoretical and applied are fine.
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1answer
57 views

Extract clusters from a graph of absolute-distance edge

I don't know if I have formulated this problem right: I have tons of items and the distances between each pair of them. Feeding this data into some visualization tool, I am able to create a nice ...
3
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1answer
367 views

How to train an L2-regularized L1 Hinge Loss SVM using vowpal wabbit?

I'm trying to train an L2-regularized L1-hinge loss SVM using vowpal-wabbit. I use the following commands to train and test on the splice dataset: ...
5
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2answers
263 views

Do RBF kernel matrices tend to be ill-conditioned?

I use RBF kernel function to implement one kernel based machine learning algorithm(KLPP), the resulting kernel matrix $K$ $$K(i,j)= \exp\left({\frac{-(x_{i}-x_{j})^2}{ \sigma_{m}^2}}\right)$$ is ...
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1answer
31 views

a question about kernelized locality preserving projections

kernel LPP is of form: $$\min_{\alpha} \ \alpha^{T}KLK\alpha \\ s.t. \ \alpha^{T}KDK\alpha = 1$$ and it eventually results in solving generalized eigenvalue problem below: $$KLK \alpha= \lambda KDK ...
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0answers
21 views

How do I implement a custom kernel in scikit GP?

http://scikit-learn.org/0.13/modules/gaussian_process.html#correlation-models I'd like to write a kernel. How can I do that?
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1answer
100 views

How to setup a Neural Network?

I have a completely beginner question about the setup of artificial neural networks. Basically it boils down to: How do I put in data and get results? For example, classification: let say I have ...
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1answer
57 views

Confusion related to svm optimization

I was reading thispaper related to kernel SVM. It states Support Vector Machine (SVM) (Cortes and Vap- nik, 1995) as the state-of-the-art classification algo- rithm has been widely applied in ...
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0answers
65 views

How to create synthetic data from known weights

I'm doing some machine learning where I have lots of data and through optimization I'm trying to learn the weights for the model. I'd like to check that my learning actually works correctly. For that ...
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1answer
49 views

Confusion related to convexity of a problem

I was reading this paper related to Multiclass Classification with Multi-Prototype Support Vector Machines - paper However, I am having difficulty in understanding why they have mentioned the ...
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0answers
75 views

Determining optimal number of clusters and Davies–Bouldin Index?

I'm trying to evaluate what is the right number of cluster needed for clusterize some data. I know that this is possible using Davies–Bouldin Index (DBI). To using DBI you have to compute it for any ...
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3answers
1k views

Python OSS alternatives for Matlab Neural Network Toolbox. Any intercomparisons?

I'd like to be independent of commercial software for my scientific work. I find a dependence an commercial packages such as Matlab and its toolboxes unsatisfactory, because I do not know if I will ...
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1answer
88 views

classification machinery needed

Consider a set of 7D vectors. Each vector belongs to one of four classes. After mapping to 3D with PCA and coloring each point according its class the dataset looks like as shown below: For the ...
2
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1answer
72 views

Optimality criterion of PCA via recovered distances

It is stated in http://users.eecs.northwestern.edu/~yingwu/teaching/EECS510/Reading/Williams_NIPS01.pdf that the PCA mapping from $h$-dimensional data to low $k$-dimensional space minimizes ...
3
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1answer
848 views

Logistic regression with Python

I am trying to code up logistic regression in Python using the SciPy fmin_bfgs function, but am running into some issues. I wrote functions for the logistic ...
3
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1answer
68 views

Improve optimization over 'mapping' of indices

I have two tables at my disposal, one work dataset and one reference dataset. Each dataset has got two columns, lets say these are fields A and B. I would like to associate the rows in the reference ...
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0answers
47 views

Framework for reinforcement learning for games

[I hope this is the correct place to post - if not, please feel free to migrate the question to another site]. I would like to build a computer program that will play games effectively, and I want to ...
2
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1answer
754 views

fmincg implementation in Python

I'm trying to re-implement Neural Networks in Python. I implemented the cost function and the backpropagation algorithm correctly. I have checked them by executing its Octave equivalent code. But ...
4
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1answer
565 views

Using scipy.optimize to implement a neural network with back propagation

My problem is something similar to this. I'm trying to implement a (Neural Network) Cost function, Back propogation algorithm in Python. The Neural Network has 3 layers. Hence 2 parameters to ...
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1answer
71 views

neural networks: multilayer on-off perceptrons

This article says that all any multilayer perceptron with a linear on-off functions for all the neurons can be reduced to a two-layered perceptron. Now, consider a two input/one output perceptron. ...
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1answer
47 views

Finding most informative feature subsets given dataset, clustering algorithm and gold standard partition

I have an $n \times m$ matrix of data $\mathbf{D}$ as well as a $k$-partition $P$ of $n$ indices each representing a row in a dataset. Assuming an arbitrary clustering algorithm $A$, I would like to ...
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1answer
99 views

Adaptive Linear Algebra Libraries

After reading the first answer here about how the best way to find the most performant sparse solver is to try almost everything, I began to wonder if there was any past work on libraries or research ...
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2answers
93 views

Handling inconsistent solutions obtained by PCA

In order to achieve a 2D representation $X\in\mathbb{R}^{n\times 2}$ of some high-dimensional data residing in $Y\in\mathbb{R}^{n\times k}$, I use PCA:$$X=Y\cdot U,$$where $U\in\mathbb{R}^{k\times 2}$ ...
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1answer
69 views

Normalizing axes prior to PCA

For a given centered configuration of points $X\in\mathbb{R}^{n\times 3}$, the covariance matrix is denoted by $S=\frac{1}{n}X^TX$. Recall that the 2D PCA solution is obtained by $Y=X\cdot U$, where ...
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1answer
293 views

How to find the number of principal components that lead to the smallest generalization error?

I am working on a paper part of which is the application of validation rules to find how many principal components give us the least generalization error. The concept goes more or less like this: ...
2
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2answers
88 views

A sufficient number of distances to recover relative positions of n points

On several places I found different claims on a sufficient number of distances to recover relative positions of $n$ points in $d$-dimensional space. For instance, work from ...
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2answers
140 views

Predict runtimes for dense linear algebra

I would like to predict runtimes for dense linear algebra operations on a specific architecture using a specific library. I would like to learn a model that approximates the function $F_{op} \;::\; ...
12
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3answers
2k views

Apply PCA on very large sparse matrix

I am doing a text classification task with R, and I obtain a document-term matrix with size 22490 by 120,000 (only 4 million non-zero entries, less than 1% entries). Now I want to reduce the ...
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0answers
534 views

weka - normalize nominal values

i have this data set: ...
9
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2answers
580 views

Calculating Lagrange coefficients for SVM in Python

I'm trying to write a full SVM implementation in Python and I have a few issues computing the Lagrange coefficients. First let me rephrase what I understand from the algorithm to make sure I'm on the ...
5
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1answer
110 views

Using an approximation algorithm to adapt parameter values of a given algorithm

Problem: I have an incremental online clustering algorithm which need 4 parameters that should be specified by the user before execution. The algorithm will gives "good results" if "a good parameter ...
4
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1answer
363 views

Diffusion kernel “guide”

Diffusion kernels are kernels which "project" information about graphs into $R^n$ so that certain machine learning techniques can be performed. I have read through this paper and feel fairly ...
5
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3answers
164 views

Testing for stability of a simulated dynamical system

Background and question I often work with simulations of dynamical systems and I usually track a single parameter $x$, such as the number of agents (for agents based models) or the error rate (for ...
3
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2answers
696 views

Applying same feature selection to multiple data sets with Weka

I am using the Weka workbench to train a protein fold classifier. I imported my training data into Weka and performed PCA-based feature selection. This seems to have worked fine, but now I cannot ...
4
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1answer
121 views

Looking for an understandable discussion of creating Maximum Entropy classifiers

Texts, articles, and papers on Maximum Entropy Classifiers tend to come in two varieties: the more popular "upper level", and the more technical. The popular variety are good at explaining the ...