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

learn more… | top users | synonyms (1)

2
votes
1answer
36 views

Chi Squared Kernel and Faster implementation

There is a good implementation of Chi-Squared Kernel in http://www.vlfeat.org/matlab/vl_alldist2.html But this implementation is very slow when input data is huge. This implementation doesn't accept ...
1
vote
1answer
29 views

Comparing and evaluating various machine learning methods

I am not expert in this area so please bare with me. Is it possible to somehow evaluate the success rate of machine learning algorithm/methods. I suppose it could be done this way: Give a various ML ...
0
votes
0answers
19 views

Loss function for Random forest

I am working on a random forest model in R and want to use a different loss function from the default. Does random forest implementation in R allow for arbitrary loss functions?
0
votes
0answers
52 views

Significance of explanatory variables in Bayesian models

I was wondering if there is a general way to handle parameters of which posterior distributions include zero. Should one remove these parameters and refit the model? E.g. You fit a regression model ...
1
vote
0answers
32 views

chi square test for large data sets

I use the Chi-square test for feature selection. I use it only when all entries in the contingency table are greater then 5. Is that the correct approach statistically? What happens for example, if ...
1
vote
0answers
30 views

How to run an iteration with optim in R? [closed]

Can anyone tell me how to run an iteration in R? I have been trying an iteration but without success. The reduced form of the code is given below. I will explain briefly what i am trying to acheive ...
0
votes
0answers
30 views

How to implement Kernel density estimation in multivariate/3D

I have dataset like the following fromat and im trying to find out the Kernel density estimation with optimal bandwidth. ...
0
votes
1answer
30 views

Hyperparameter Tuning - What is possible in terms of accuracy gain?

A question from a newbie: I played around with parameter tuning (grid, random search) in R (caret, xgboost) and my observation is as follows: in terms of accuracy gains I was able to get 3 - 7% but ...
2
votes
1answer
59 views

Chernoff Bound: Prove that $P[u \geq \alpha] \leq (e^{-s\alpha} U(s))^N$

Let $u_1, ..., u_N$ be random variables, and let $u = \frac{1}{N} \sum_{n=1}^N u_n$. If $U(s) = E_{u_n}(e^{su_n})$ (for any $n$), prove that $P[u \geq \alpha] \leq (e^{-s\alpha} U(s))^N$. $s > 0$ ...
1
vote
0answers
24 views

How to find the threshold that minimizes the (weighted) mis-classification rate?

To use a logistic regression model for doing prediction, let \begin{equation} \hat Y_i= \begin{cases} 1 &\mbox{if $P(Y_i=1|X_i)>\alpha$}\\ 0 &\mbox{if $P(Y_i=1|X_i)\leq\alpha$} ...
1
vote
0answers
43 views

How do I calibrate iPhone in a car? [closed]

I'm trying to make an app for detecting car maneuvers based on accelerometer/gyro data. To build a good classifier my data should be aligned to the car axes: I developed an algorithm that is ...
4
votes
1answer
44 views

Having trouble creating my Neural Network inputs

I'm currently working on a neural network that should have N parameters in input. Each parameters can have M different values (discrete values), let's say {A,B,C,…,M}. It also has a discrete number of ...
1
vote
0answers
25 views

What visualizations do people use to debug a machine learning model?

Imaging I am refining a model. What visualization can I rely on to help me identify an error, e.g. feature deficiency, data bias? A few graphs I am aware of include: confusion matrix, ROC, learning ...
3
votes
1answer
56 views

what is difference between t-test and 10-fold validation?

one of famous significant test is t-test which can conclude is our result by chance or not using previous results and their variance. Also when we use 10-fold validation we break our dataset to train ...
0
votes
0answers
28 views

Lemma needed for my machine learning research

Say $\sigma_1, \sigma_2, \dots, \sigma_m$ are i.i.d distributed $\pm1$ variables. How do I show that for any choice of $S_1, S_2, \dots, S_d$ subsets of $\{1, 2, \dots, m\}$, the expectation of the ...
2
votes
2answers
91 views

Cost function in OLS linear regression

I'm a bit confused with a lecture on linear regression given by Andrew Ng on Coursea about machine learning. There, he gave a cost function that minimises the sum-of-squares as: I understand where ...
-1
votes
1answer
110 views

Data Science & Stats questions [closed]

I have a few probability and stats questions and was hoping if someone could help in answering those. 1). Imagine there is a square. There is an ant at one corner of the square. At each step it ...
0
votes
1answer
43 views

What does log-uniformly distribution mean?

When someone say a data is sampled from a log-uniformly distribution between 128 and 4000, what does that mean? How that different to sampling from a uniformly distribution? See this paper: ...
4
votes
1answer
72 views

Online mean shift algorithms

I am looking for an online algorithm which can identify mean shifting in a time series quickly, I have seen some algorithms that do so but they require 50+ samples in order to flag that the mean has ...
2
votes
1answer
43 views

A statistical test to measure the importance of features?

I'm currently trying to assess importance of the features for my classifier. The situation is the following: first I train my classifier with all of the features I have and tested on a test set . Then ...
0
votes
0answers
34 views

How to qualify which features to use in a predictive model?

When building a predictive model, it's well established that picking/building the right features will draw the line between failure and success in the forecasting task. That's said, some people ...
0
votes
1answer
89 views

How to minimize class weight vector of Random Forest Classifier using CV

What I'd like to do is optimize the class weights of a Random Forest Classifier (using python and the sklearn library) for multiclass classification, in which different misclassification errors have ...
0
votes
0answers
17 views

Is it possible to achive low error on MNIST using Random Ferns?

I'm new in machine learning and i want to study how to use random ferns. I read this paper Fast Keypoint Recognition in Ten Lines of Code and implement simple version of algorithm. But then I tried ...
3
votes
1answer
59 views

Exact definition of Maxout

I've been trying to figure out what exactly it meant by the "Maxout" activation function in neural networks. There is this question, this paper, and even in the Deep Learning book by Bengio et al., ...
0
votes
1answer
30 views

How do I combine various factors/variables to a single factor/variable

I have various products and for each product I have 5 types of cost(not just monetary cost) variables associated with it, the value of each variable for any product is a positive integer. I want to ...
0
votes
0answers
29 views

How to use machine learning to predict future workload?

I am trying to predict the future workload based on below dataset: I have data for a few days and I am trying to predict future requests. This is my first machine learning project. I appreciate ...
0
votes
1answer
30 views

Only one support vector in a linear svm kernel

I am new to SVM, but I would like to understand certain things. Firstly, when dealing with multiclass classifications, I have a large number of support vectors as proven by R. However, when I run ...
2
votes
3answers
85 views

Elasticity calculation on real data

I have data set on several SKU (within one Brand, which were divided by 3 groups) daily demand and prices during one month. Prices were fixed in this period. After this period we begin to increase ...
0
votes
0answers
16 views

Exponential Smoothing with Causal Regressors

I am trying to develop several approaches to analyze the effect of covariates on retail sales . the first approach i am trying to use is exponential smoothing with regressors (for its simplicity to ...
1
vote
0answers
22 views

Resources for online / continuous learning neural network

this is my first post here so please point me in the right direction if the question isn't appropriate. I am interested in learning more about 'online' or 'continuous learning' neural networks - that ...
0
votes
1answer
36 views

Temporal features in survival analysis

I'm modeling customer churn, experimenting with both Aalen Additive and Cox Proportional Hazards models, using the lifelines package in Python. If this were a more ...
1
vote
0answers
8 views

Is there an supervised learning method (a classifier) that can account for unobserved heterogeneity like a mixed logit can?

I'm just starting to teach myself various machine learning techniques. My background is in more "classical" statistics. I've got an analysis that I've done using a mixed logit to predict linkage in ...
0
votes
0answers
16 views

Comparing probabilities of two predictive models

Someone has already asked this question. But it is not answered. I have 10 logistic regression models for 10 different product categories. Then i need to come up with the best product to be offered to ...
0
votes
0answers
14 views

How does micro precision work

I am trying to figure out how micro precision works and have followed some tutorials online. But some things don't make sense at all I copied the part of the text from a website online ...
1
vote
1answer
45 views

Visualizing SVM results

I would like to know if there are ways to visualize the separating hyperplane in an SVM with more than 3 features/dimensions. Normally, classification plots are possible with 1,2 and 3 dimensions (see ...
1
vote
1answer
46 views

Need an explanation on variable notation used in “The Elements of Statistical Learning”

I have just downloaded a free ebook The Elements of Statistical Learning. It's been recommended by many so I decided to give it a go. But I found explanation on denoting variables confusing. In ...
0
votes
0answers
44 views

The bias neuron in a neural network : Is my understanding right?

I was just going through Neural-Network tutorials and I have some question regarding Bias neuron :- 1.] Is the act of introducing bias neuron same as introducing the X(index 0)=1 in the logistic ...
0
votes
1answer
42 views

Evaluating significance of predictors in Machine Learning using R

I've bee using R for predictive analytics and here is the issue: I'm trying to predict the species (E1, E2, E3 and E4) of an animal using as predictors a set of categorical (factors) (NO1, NO2, NO3, ...
1
vote
1answer
56 views

Machine learning tutorials / examples on data sets larger than a terabyte

I am trying to gather a list of practical ML examples / tutorials on more than a terabyte of data. I'm particularly interested in feature extraction from large data sets that involves aggregation (the ...
0
votes
0answers
20 views

Label permutation with cross-validation

I wanted to find out if my machine learning application is prone to overfit. I first did an actual analysis with three diffent classifiers, and then repeated the whole process a few hundred times with ...
0
votes
0answers
12 views

Ttests for DNA sequences

Let's say I have two sets(1000 sequences in each set: set1 and set2) of independent DNA sequences of length 30. I created a HMM model by using DNA sequences in set1 which calculate Prob(Seq/Model). It ...
3
votes
2answers
83 views

Evaluation and optimization in machine learning

I am reading the article "A few useful things to know about machine learning" by P. Domingos. Now, I am confused about two of the three components of learning, i.e., the evaluation and optimization. ...
0
votes
1answer
64 views

Understanding logistic regression

I am taking the coursera machine learning course by Andrew Ng and have run into some issues. I do not understand why the answers are like this? The equations seem to me the same but the graphs are ...
0
votes
0answers
25 views

How to detect contradictory examples in training data

I want to implement an online learning classification algorithm. Therefore I want to detect contradictory examples in my training data once the user wants to add a new example to the training data. ...
2
votes
3answers
49 views

Comparing four classifiers

I have trained and tested four different classifiers, and I would now like to compare them. The classifiers have accuracies 95, 90, 81, 75. I know that there is no unbiased estimator of the variance ...
0
votes
0answers
41 views

Q-Learning using ANN with continous action and variable-length state

The question is basically What should I do if state vector has variable length? If the action is bounded and continuous, how can I obtain max(Q(state,action)) without using painfully slow global ...
3
votes
0answers
38 views

Drunken dancer. Best fit of an experimental trajectory to model trajectories with large variations in independent variable

I have several model point trajectories (choreographies), describing movement of a model dancer in a one (for simplicity) dimensional space versus time. I am also observing a movement of a real ...
2
votes
1answer
73 views

A list of cost functions used in neural networks, alongside applications

What are common cost functions used in evaluating the performance of neural networks? Details (feel free to skip the rest of this question, my intent here is simply to provide clarification on ...
1
vote
0answers
14 views

Imposing singular value constraints on recurrent neural networks

Apologies for beginning with what are surely very old results, to make clearer my thinking. First, note that any multi-layer perceptron (MLP) may be represented as a recurrent neural network (RNN). ...
0
votes
0answers
33 views

10-fold Cross-validation vs leave-one-out cross-validation

I'm doing nested cross-validation. I have read that leave-one-out cross-validation can be biased (don't remember why). Is it better to use 10-fold cross-validation or leave-one-out cross-validation ...