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

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14 views

Time series with multiple subjects and multiple variables in R

I'm having trouble finding a time series technique to deal with a data set I am working on. It contains multiple subjects and multiple variables, not all of which will likely be part of the time ...
3
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3answers
64 views

Explanation on a Minsky's critique on statistical learning related to XOR

I was listening to the first session of society of Minds by Minsky (2011) and he mentions at some point around minute 48 the following: "...lots of statistical learning tools is good for lots of ...
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5 views

SIFT rotation invariance

In Scale-Invariant Feature Transform, keypoints in an image are extracted which are invariant to scale, rotation and translation. The keypoints contain information on the scale and gradient of a given ...
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2answers
202 views

Heuristic Feature Selection for Gradient Boosting

I originally posted on Stack Overflow and was told to move it here. If I am trying to select from two different sets of features for a Gradient Boosting Machine, but I do not want to run through ...
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2answers
118 views

Non-linear projection in self organizing maps

I have difficulty understanding how self organizing maps (SOM) are doing dimensionality reduction. Can anybody provide a useful explanation to me? Suppose we have 20 training data points in 50 ...
2
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1answer
82 views

Detecting strong currents in a sparse directed graph

I have a very large, sparse, weighted, directed graph. The structure is such that it mainly consists of strings of nodes connected with highly weighted edges. These strings can be connected by weak ...
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0answers
17 views

Observed versus hidden variables for Bayesian network in this particular context

I am a novice in Bayesian networks. I have a problem which is best described (at least I think so) in the following story. One wants to predict earthquakes. Let's say it has 5 variables, the last one ...
3
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2answers
118 views

Anomaly detection with a multivariate Gaussian vs. PCA + univariate Gaussians

In Andrew Ng's Machine Learning Coursera Class, he covers anomaly detection in multiple dimensions for both independent univariate Gaussians and multivariate Gaussians, the latter being more costly ...
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2answers
539 views

Model-based learning algorithm for recommendation engine

Can you please suggest me a good model-based learning algorithm to recommend items to the user? Is there any open source implementation available on model based learning algorithm? I am sure Apache ...
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34 views

When to use K mean clustering and hierarchical clustering algorithm? [on hold]

Can you please tell me when to use the K-mean clustering and hierarchical clustering algorithm and what is the different between them... Regards, Rahul
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2answers
18 views

Inferring on an unknown number of function approximation

I want to ask whether a procedure to do the following job exists (or whether it makes sense for it to exist). First, assume we have $k$ functions $f_1,...f_k$ that have the same domain and range. ...
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0answers
26 views

Find distribution of Bus arrival time

I am currently working on a problem in my research which can be modeled into the following question: Let's say I have a rich dataset with values for the variable $A$ which is equal to ...
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0answers
8 views

Machine learning/random forests with noisy response data

Machine learning techniques like random forests seem to assume that the responses in the training set are known perfectly. Specifically for regression applications, it seems one needs to account for ...
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0answers
8 views

Viability of software dev - Use of and requirements of NN

Hello I would like to know this two things regarding the viability of producting a software, so: 1) Are available on internet some OCR libraries for free? Can I train my own NN having only a laptop? ...
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2answers
102 views

How to prove that the manifold assumption is correct?

In machine learning, it is often assumed that a data set lies on a smooth low-dimensional manifold (the manifold assumption), but is there any way to prove that assuming certain conditions are ...
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1answer
22 views

What is a good model for revenue managment / price optimization problem

I am trying to create a dynamic pricing model to optimize revenue for a hypothetical business. Lets say I have an application that connects dog walkers to people who want to pay for their dog to get ...
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2answers
123 views

Class labels in data partitions

Suppose that one partitions the data to training/validation/test sets for further application of some classification algorithm, and it happens that training set doesn't contain all class labels that ...
2
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1answer
41 views

One model performs better than the other. How to measure if it is statistically significant?

So, let's say that I train two models on the same dataset. I run the experiment once and I get the following results: Using a Neural Network I get an AUC ROC of 0.941. Using Random Forest I get an ...
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2answers
343 views

How to define train and test sets in financial time series for estimating machine learning parameters

After reading some material, I found few options for defining train and test sets: Just splitting with no change. Accumulating/moving window of train set. Leave a relatively small (warming) period ...
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0answers
8 views

svmlight for unbalanced data [closed]

I'm using svmlight for multiclass classification using one vs rest strategy. I'm having highly unbalanced data. One data set has 5000 and other set has 500.How to train this unbalanced data in ...
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1answer
26 views

make prediction with HMM

I want to use HMM to make some prediction. say $O$ is the observation, $S$ is the hidden states, and I know how to train the model with forward-backward algorithm. I just get confused with how to ...
2
votes
1answer
48 views

K-means clustering feature selection

I have a set of English and foreign language documents that I would to perform k-means clustering on to find document groups by topic. These documents are concatenated social media comments for ...
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1answer
31 views

How to normalize filters in convolutional neural networks?

Usually when convolving images the elements in the filter sum to one. Does this creteria enforce in convolutional neural networks? If yes, How?
0
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1answer
359 views

Clustering text with python

I asked on stackoverflow but they suggest me to move here for better answers. I copy paste the question. I decide to play a little with similarities and clustering text. I have already create the ...
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2answers
175 views

Scaling the backward variable in HMM Baum-Welch

I am just trying to implement the scaled Baum-Welch algorithm and I have run into a problem where my backward variables, after scaling, are over the value of 1. Is this normal? After all, ...
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2answers
35 views

What is the difference between a neural network and a perceptron?

Is there any difference between the terms "neural network" and "perceptron"?
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1answer
36 views

Dimension Reduction

I have a $N \times M$ matrix, the rank of matrix, $r$, is near to $min(M,N)$. I want to minimize the rank by removing some of the rows or columns to get $r << min(M,N).$ The goal is to achieve ...
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1answer
61 views

Are there any contemporary uses of jackknifing?

The question: Bootstrapping is superior to jackknifing; however, I am wondering if there are instances where jackknifing is the only or at least a viable option for characterizing uncertainty from ...
3
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1answer
53 views

What does the k-value stand for in a KNN model?

What is the k-value in a KNN classification model? Is K the number of Clusters?
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2answers
161 views

Newbie to neural networks

Just starting to play around with Neural Networks for fun after playing with some basic linear regression. I am an English teacher so don't have a math background and trying to read a book on this ...
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1answer
101 views

In a neural network of n features which predict a continuous variable X, how to tell the feature which contributes the most to the output value X?

Say I have a neural network which uses some input features say N, some inut layers say L which predict a continous variable say X. Can we say which features or combination of 2 features of the initial ...
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0answers
27 views

What are the potential disadvantages of doing kernel PCA?

I was trying to learn more of the motivation around kernel PCA. Its clear to me that one might need to change the representation of the data if it lies in a non-linear space, hence, the projection ...
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1answer
62 views

How to solve this problem on Curse of Dimensionality problem - Nearest Neighbours

I have started learning classification techniques and trying to solve the problems from the book Introduction to Statistical Learning. While currently working on the which is based on Curse of ...
2
votes
1answer
311 views

Weighted covariance matrix using kernels

I would like to create a weighted covariance matrix (say 5 variables) using 3 different time points where the weights come from a kernel function (can be normal, triangular, etc.) but I'm not ...
0
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1answer
24 views

Is there AUC for neural network?

I am confused about how to calculate AUC for neural network with a softmax classifier. For example, I know that for SVM, we can change the threshold value and determine the AUC. WHat about in neural ...
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0answers
9 views

Bayesian network overfit - number of features and examples

For a dataset consisting of 150 examples (mostly binary features) what would be the number of features needed so that a Bayesian network doesn't overfit? I know there is no exact answer and I've ...
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6 views

Number of parameters in multinomial logistic regression

In Chapter 10 (Directed graphical models) of Murphy's Machine Learning text, the author claims that multinomial logistic regression has $O(K^2 V^2)$ parameters, where $K$ is the number of discrete ...
6
votes
2answers
993 views

TF-IDF cutoff percentage for tweets

I'm currently trying to analyze Tweets and classify them as either positive, negative, or neutral using the NLTK library in Python. I can see that there's potential in the approach that I'm taking, ...
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0answers
23 views

What are the most interesting, new hot topics in machine learning for seminar and later for thesis? [closed]

I'm in an informatics master student in Palestine Polytechnic University, I have a seminar course this semester i cant decide the topic to search in, especially that i want it to be my thesis topic ...
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16 views

Convolutional Neural Network Performance - Cats & Dogs

I am currently experimenting with a Convolutional Neural Network, trying to get a good performance on the Cats & Dogs challenge at Kaggle. By now, the best result I could get using my network was ...
2
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1answer
212 views

Comparison of two classifiers based on precision/recall/F1 only?

For two classifiers h1 and h2 I have the precision, recall and F1 score as a percentage (along with the original labeled data set that they were tested on). If I had access to which samples each ...
4
votes
1answer
175 views

Why do we divide by the standard deviation and not some other standardizing factor before doing PCA?

I was reading the following justification (from cs229 course notes) on why we divide the raw data by its standard deviate: even though I understand what the explanation is saying, it is not clear ...
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19 views

Suitable Model for predicting flight delays in R [closed]

I want to predict the flight delays.Which classifier or which machine learning algorithm i have to use for predicting the flight delays in R and please guide me how to find the accuracy of that ...
0
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1answer
35 views

combining multiple classifiers common features

Can multiple binary-classifiers be combined to produce a final output if their feature sets have some common elements? How will this influence the accuracy?
4
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2answers
807 views

Gaussian Processes: How to use GPML for multi-dimensional output

Is there a way to perform Gaussian Process Regression on multidimensional output (possibly correlated) using GPML? In the demo script I could only find a 1D example. A similar question on CV that ...
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0answers
3 views

removing batch effect when combing patient's data into a large cohort

I have some clinical data quantifying severity of disease for patients from 3 different hospitals. Basically, the patient severity vector for each hospital looks like below: ...
2
votes
1answer
140 views

Machine-learning input data distribution

I'm trying to build a binary 1/0 ML classification algorithm, and was thinking about how to set up the input dataset. If the event I want to predict (the 1's) occur relatively less frequently in the ...
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1answer
391 views
0
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121 views

Classification accuracy

I am classifying text based on news headlines and I am achieving accuracy up to approx 80%. I want to improve it more. But issue is that when I calculate the same with synonyms using the code below: ...