0
votes
0answers
2 views

how to implement linear or non linear regression for 3d position estimation in Matlab?

I am a beginner in Machine Learning. For my project I need a regression algorithm that can estimate the 3D position of a device based on some constrains (more over inputs). I know how to implement ...
1
vote
1answer
42 views

For a model like this what performance measures can I calculate and how?

Methods: From the machine learning literature, I understand different parameters can show performance of model in machine learning. I would briefly expand my understanding with confusion matrix: ...
0
votes
1answer
14 views

Regression-tree Tuning in a Streaming Setting

Some time ago I went through a NIPS 2013 paper Regression-tree Tuning in a Streaming Setting. The paper proposes a tree-based regressor. Is there any implementation of this algorithm available? (At ...
1
vote
0answers
9 views

How to assess the importance of the features which come from intersection of features of the two models?

I have two models from two different data sets. Model 1 contain 50 features and model 2 contain 40 features. the intersection of features of model 1 and 2 is 10. so how can I assess the relative ...
0
votes
1answer
12 views

How to compare the nested models which each of them comes from diffrent dataset?

I have four nested models.Every of them learned from different data sets. now I want to compare these models together.normally people try to compute the F-satistics. But for my case, it's bit harder, ...
3
votes
2answers
32 views

What model would be appropriate for predicting electrical consumption given multiple (mostly) independent variables?

I have about 1000 samples worth of daily electrical consumption for a building. I'd like to build a predictor based on a number of observable inputs, including: daily temperature (continuous) hours ...
0
votes
1answer
49 views

How to compare models from different but related datasets?

I'm building regression models on four the different but related data set and at the end, I want to test the significance of models. Since my models are built in a different data set, it's not ...
1
vote
1answer
18 views

Regression Gaussian Estimates instead of points

I am using a support vector regression is order to get estimates of a variable y. I want to receive a probability distribution of my estimates and not just point estimates. I want to predict Gaussian ...
1
vote
0answers
21 views

Binary classification of dated text documents with seasonality

I have a collection of training documents with publication dates, where each document is labeled as belonging (or not) to some topic T. I want to train a model that will predict for a new document ...
0
votes
0answers
32 views

Conditional or Joint Probability under Various distributions

In various statistical models the baseline equation (like in Naive Bayes $$\mathrm{classify}(f_1,\dots,f_n) = \underset{c}{\operatorname{argmax}} \ p(C=c) \displaystyle\prod_{i=1}^n p(F_i=f_i\vert ...
0
votes
0answers
16 views

Regression line fit for linearly increasing data with manual reset

I've a linearly increasing time series dataset of a sensor with value ranges between 50 to 150 on which I've implemented a simple linear regression algorithm to fit a regression line, and I'm ...
1
vote
2answers
183 views

Estimate ARMA coefficients through ACF and PACF inspection

I know that this is probably a question that's been asked plenty of times, but i haven't seen an answer that's both accurate and simple. How do you estimate the appropriate forecast model for a time ...
0
votes
0answers
26 views

What machine learning tool is best suited for taking time series data as well as descriptive data and making a binomial classification

I have an interesting task of utilizing log data from computer servers in a server farm and predicting if a particular server is likely to fail in the next 24 hours. My data set will be comprised of ...
1
vote
1answer
42 views

Estimation in Naive Bayes

I have a very silly question. In Multinomial Naive Bayes Classifier, which parameter estimation do we use, is it Maximum Likelihood or Maximum A Posteriori? If any one of the esteemed members may ...
0
votes
1answer
29 views

How to compare the significance of two models from two different datasets?

I have two different regression models which I learned from two different data sets. Is there any statistical method which shows the significance of models based on the number of parameters and cross ...
0
votes
0answers
18 views

What are the best criteria to select the model for Lasso regression?

I have two different formulations of the Lasso regression for the same problem. For each formulation, I selected the best model based on cross validation error. But Now, I want to compare two models ...
1
vote
1answer
31 views

Is there a stats tool for this analysis I run in excel?

I am trying to find a statistical or machine learning tool that replicates this analysis I am doing manually in excel. Each row in my data set is a user. ...
7
votes
2answers
317 views

Why would anyone use KNN for regression?

From what I understand, we can only build a regression function that lies within the interval of the training data. For example (only one of the panels is necessary): How would I predict into the ...
0
votes
1answer
47 views

Regression model for $f(x_1, x_2) = a + b x_1\log x_2$

Which regression algorithm do I need to use to fit the coefficients of $f(x_1, x_2) = a + b x_1\log x_2$? Will linear regression with an independent variable $x_1 \log x_2$ work?
0
votes
0answers
18 views

Classification More Robust Than Regression

Are neural networks using classification more robust / reliable than using regression to produce a single value? The only reason I would think so is that it would be easier for the network to adjust ...
1
vote
0answers
29 views

Random Forest regression model in R and data overfitting

I have trained my random forest model on a 74,000 training examples where each example consists of two proteins Amino Acids sequence (20 characters) and some numeric values representing the similarity ...
1
vote
0answers
47 views

Online model training in R, without a static data

Let's say I have a model in R, a regression tree created by "glm",using "data1" dataframe: Model1 = glm(DepVar ~ . ,data=data1,family="binomial") Is there a way ...
0
votes
0answers
27 views

How to handle the error of glmnet package for non-positive lambda?

I'm using glmnet package to learn regression models,it works fine, but for some models, I face an error and my script stops running. Here is my effort: ...
0
votes
1answer
111 views

Intuitive explanation of Bayesian logistic regression?

I'm looking for an intuitive explanation of Bayesian Logistic Regression (I'm using it for texts if that's relevant). It seems that this article presents it, but it's, uh, way too mathy. Thanks!
1
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0answers
47 views
1
vote
0answers
46 views

How is L2 Boosting Different from a Big Regression Tree?

I'm learning about boosting. I think I understand how adaptive boosting works for classification. I'm trying to get some intuition for regression boosting. At each iteration, adaptive boosting ...
3
votes
1answer
311 views

Choosing the right forecasting technique

I'm currently attempting to forecast visitor data for stores. My dataset includes daily visitor totals of three years. Note that the dataset isn't complete (stores can be closed for a few days, etc). ...
0
votes
0answers
8 views

Learning a multivariate polynomial with dependent coefficients

I have a polynomial of the form $K^2((a-i)^2 + (b-j)^2 + c^2) = (ct)^2$ where $a,b,c,t$ are unknowns. I have multiple observation points for the values of $i,j,\&\ K$. Can I use some technique ...
0
votes
1answer
17 views

Expected error of best possible linear fit?

In my textbook, there is a statement mentioned on the topic of linear regression/machine learning, without a proof or rigorious justification, which is simply quoted as, Consider a noisy target, $ ...
0
votes
0answers
52 views

Google Prediction API Flaws

I have been testing the google prediction api https://developers.google.com/prediction/ It seems to be excellent, i gave it 5 features so it can predict a regression problem, the API fitts the data ...
0
votes
1answer
80 views

Explanation of the Regression Plot in the Matlab Neural Network Toolbox

What does the Regression Plot in the Matlab Neural Network Toolbox show? I thought I understood it when I looked at a univariate regression plot, but I've just plotted one for multivariate regression, ...
1
vote
0answers
36 views

How should I handle variables whose data points have varying degrees of predictive power?

I'm trying to determine which type of learning algorithm is best for making predictions on my data. My data set consists of several independent variables, each of which is accompanied by an ...
3
votes
3answers
319 views

Any algorithms better than polynomial regression

I am trying to fit a baseline through my data, and I am not getting close enough with polynomial regression. I used gradient descent to set the parameters. Are there any other ways or algorithms that ...
0
votes
1answer
47 views

Denormalizing Data

I am applying Polynomial Regression to my data, however the parameters theta were always =0, i noticed that my y data or output is too large in the order of 100000 so i normalized y, i got very good ...
1
vote
0answers
52 views

How can I improve the accuracy of my logistic regression code, which tests the accuracy using the 10-fold cross-validation technique?

How can I improve the accuracy of my logistic regression code, which tests the accuracy using the 10-fold cross-validation technique? I have implemented this code using ...
3
votes
1answer
112 views

How to choose the right number of parameters in Logistic Regression?

I am studying Andrew Ng's Machine Learning lecture notes. I understand either we can manually choose the number of parameters, or we can use regularization to make it correctly fit. I was wondering ...
0
votes
1answer
101 views

L1-norm cost function for Neural Network. (Regression)

I am trying to build a regression model using a neural network. The final cost measure is the mean absolute error (MAE) on the output (one output unit, 200 input units). Right now all my hidden units ...
0
votes
0answers
19 views

How can I use logistic regression with categorical variables? [duplicate]

I want to use logistic regression for binary classification on a dataset. I have 14 features in the dataset, and all but one are continuous. I have one categorical variable that represents a ...
2
votes
1answer
143 views

Final Model Prediction using K-Fold Cross-Validation and Machine Learning Methods

Similar threads: Feature selection for "final" model when performing cross-validation in machine learning Choosing a predictive model after k-fold cross-validation My question is quite ...
1
vote
3answers
147 views

Leave One Out Cross Validation

I tried to implement the Leave One Out Cross Validation (LOOCV) method to get me a best combination of 4 data points to train my model which is of the form: Y= a + b X1 + c X2. Where a, b and c are ...
1
vote
1answer
52 views

Model fitting to data by using machine learning algorithms?

I am trying to fit an equation to data. I know the form of the equation but I need to know constants parameters in the equation. I used non-linear fitting and optimization techniques but I could not ...
0
votes
1answer
100 views

Linear Regression Real Life Example

I am learning Machine Learning(Linear Regression) from Prof. Andrew's lecture. While listening when to use normal equation vs gradient descent, he says when our features number is very high(like 10E6) ...
0
votes
1answer
54 views

How to make stochastic gradient descent algorithm converge to the optimum?

(Background info taken from my blog) In logistic regression, the hypothesis function, which models the relationshiop between the dependent variable $P(y = 1)$ and the independent variable $X$, is : ...
1
vote
0answers
23 views

Are these descriptions of batch gradient descent algorithm conflicting each other?

The first one is from Andrew Ng The second one is from Francis Bach I might be a little confused, but why is there a summation of partial derivatives in the second description and none in the ...
0
votes
0answers
31 views

Response surface of a particular discontinuous function

I have a function IR that depends on several (maybe 100) input random variables. I know ...
0
votes
0answers
20 views

sub-questions with likert scales choices

I want to determine compliance to a certain standard in ISMS and to determine that, I have the standards started and it has sub-questions (say 2,3,4 questions), with each having a 5 point likert type ...
3
votes
2answers
159 views

How to calculate p values in logistic regression with gradient descent algorithm

In logistic regression, the gradient descent algorithm for calculating coefficients can be described this way: Until convergence, do $$ \beta := \beta + \alpha \frac{\partial L}{\partial \beta} ...
0
votes
1answer
23 views

How to Build a Foresight System?

For a research project, I'm asked to find ways to build an economic foresight system. For example, for the production of cheese. We will have data about the market indicators, like price, demand etc. ...
2
votes
0answers
55 views

Time series prediction where each datapoint has a sequence

I am Computer Science major, and new to stats, so please bear with me and point me to the right direction if what I'm asking is pretty obvious. I have a dataset, where each data point consists of ...
2
votes
1answer
89 views

Imbalanced training dataset and Random Forest regression model

I have a large dataset (>300,000 observations) that represent the distance (RMSD) between proteins. I'm building a regression model (Random Forest) that is supposed to predict the distance between any ...