Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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Forecasting daily usage of a prouct

Lets say that you have panel data, of daily consumption of product p1 of 10000 individuals. The panel data is on a daily basis for only one month, this means that $t=1,...,30$. The question is how do ...
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1answer
1k views

What does it mean when the coefficient of the squared term is negative in regression?

I am reading a research paper which models a regression model where the returns are regressed on the number of ad exposures. the equation looks something like this: $Returns = beta_1*nExp + beta_2*...
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142 views

Chose the right regression analysis

In R I have data where head(data) gives ...
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3answers
308 views

How to see which transformation is the best

In R I have data and I want to make a regression analysis, finding a function that can fit the data. So head(data) gives ...
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2answers
499 views

Simulation - identify the input parameters that impact the most the output

I am studying (via simulation) a system that has several input parameters. The output of the system is influenced by the input parameters. My goal is to identify the parameters that have the most ...
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3answers
268 views

Obtain a model where each feature vector is past few samples and labels are future few samples?

So, I have this data set where each instance is made of past 20 samples of 2 variables. Labels are next five samples. So every instance looks like this: ...
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555 views

Checking regression coefficients' stability?

I have a model with 13 independent variables (2 of them are categorical variables) and 678 observations. All of the variables are significant.I'm planning to check the coefficients stability. My ...
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2answers
4k views

Dummy coding a column in R with multiple levels

I have a dependent variable measuring the net revenue. One of the major predictor affecting this is "product" i.e. the product sold to the customer. My randomly sampled dataset contains 1.4 million ...
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422 views

Trying determining degree polynomial for polynomical regression

I'm trying to predict the birth weight baby using polynomial regression model. First what I need know what degree polynomial should fit better to my data. In order to do that I split my dataset in ...
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2answers
3k views

Use of cross validation for Polynomial Regression

I've two text files which contains my data. One text file on X axis another text file on Y axis Then using scatter function from python I did the data visualization After that, I used polyfit function ...
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1answer
246 views

Model selection by Interpreting p-value of anova function

I am trying to interpret the p-values for model selection. Here is a sample code taken from a book (An Intro. to stat. Learning, page 290, by Gareth James et al.)  Null-hypothsis: Model ...
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1answer
270 views

Kernel regression results in diverse outputs

I am using kernel regression to build a prediction model. For the same, I am using np package. It is working fine, but I observed in multiple runs on the same data, it produces different results. Why ...
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3answers
5k views

What algorithms can be used to predict the outcome of a cricket match?

I am doing a project to predict the outcome of a cricket match, I have the data that states which matches were won by whom for ODIs. [Espn data] Which algorithm could be used to predict the outcome ...
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1answer
203 views

Underlying model for prediction using different prediction variables

I have time-series energy consumption data for a duration of one-month. The frequency of data is half-hourly. The features of dataset are temperature - temperature value at particular time instant ...
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486 views

What are the strategies for feature engineering in a hierarchical/relational structured data?

I have a feature set with each feature having its own feature-set, and they are laid out in a SQL database with foreign key relationships. The target is defined on the top level feature-set and is a ...
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45 views

Coalitional effect in logistic regression and assessing explanarory variable contribution

I have a problem that could be described as logistic regression with all dichotomous variables: 1 response variable (DV) Y (I would call it later as a feature/violet star) and 5 explanatory variables (...
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1answer
151 views

Error of linear regression as a result of the coefficients

I'm trying to resolve a paradox. Suppose that I have a bunch of data points $\{x_i,y_i\}$ and calculate a slope and intercept, $m$ and $b$ such that $y=mx+b$. Also, I can calculate the error in $m$, $\...
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38 views

How to relate the regularized regression coefficients with their number in the plot?

I have a model with 13 independent variables (all of them are significant and 2 of them are categorical variables) and 678 observations. I ran the ridge regression and lasso on the data set using ...
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776 views

Regression coefficient stability measurement in a multiple linear regression particularly in r?

I have a model with 13 independent variables (all of them are significant and 2 of them are categorical variables) and 678 observations. I was wondering if there is any way to check the coefficients ...
2
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1answer
117 views

Difference between coefficient of determination and least squared error?

Where and when should I consider R^2 as a measure of goodness-of-fit for regressions? Usually I choose the least squared model as the best model. Is it possible that the least squared model does not ...
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2answers
256 views

Best tool for analyzing inventory that has binary sales outcome of yes or no

I am trying to determine a good tool that will help me generate a probability of a sale for a list of of 300,000 products. I have a table of historical sales data (with about 300,000 records) that ...
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50 views

How to interpret a dataset with a pseudo-logarithmic trend?

I am dealing with a scatterplot where I am trying to figure out the relationship between two variables, but I have so far failed to identify what the best fit could be. The presence of zero values ...
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1answer
151 views

If my data looks like this, is linear regression just never gonna be useful?

Clearly you can see that there is no linear relationship. If there was one it would be a vertical line which is not that useful. I need some type of regression rather than classification as the output ...
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510 views

Machine Learning with fixed and variable inputs and multiple outputs

I've been doing machine learning and neural networks for a couple months, and finished a 5 months online course of it last year, but I'm struggling in an specific scenario: Let's say we've got this ...
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Beginner: how to model net change given an incomplete set of input/output figures

this is my first post on the Stack Exchange site, and I'm looking for some guidance. I have a set of 10x input numbers (positive), and a set of 10x output numbers (negative), as well as the real net ...
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2k views

Why is Spark's LinearRegressionWithSGD very slow locally?

I have been trying to run linear regression with SGD that is found in Spark mllib for some time and I am experiencing huge performance problems. All examples that I was looking have number of ...
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1answer
786 views

Comparing training and validation data set Root MSE for a best subset regression?

I’ve a model with 14 dependent variables (all of them are significant) and 678 observations. I used best subset regression and validation set (33% of data for the validation) to find which statistical ...
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1answer
64 views

Ideas on cost function

[If this is the wrong place to ask this question, please let me know where I can receive better answers:)] So I'm building an internal tool for an digital media organization. The tool aims to track ...
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1answer
293 views

Hyperparameters in Gaussian Process

My academical background is in physics and analysis (PDE's), but now I'am reading about data science. I'm reading about Gaussian Process implementation in Sci-Kit Learn I could not find a simple ...
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1answer
176 views

How exactly dependent variable is expressed in terms of independent variables using Partial Least Square Regression Method?

I understand the working of NIPALS algorithm but while doing the regression using PLS how exactly the relation between known and unknown is established using Principle Component Analysis. The idea is ...
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50 views

Modified Voting Algorithm to find the best recommendation

I have to find the best 10 items from the set of items for x number of given features. I don't know what the best recommendation will be. User data is not available to validate it. After reading a ...
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1answer
69 views

Validate output

I am trying to find the top 10 useful item recommendation. Items are divided into categories and then top10 in each category is calculated. There are six features based on which a score is assigned to ...
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3answers
971 views

How to predict an approximate weekly/monthly number, when the Unique Daily Visitors for that week/month are already known

I am trying to come up with a formula or machine learning algorithm using which I can approximately predict the weekly or monthly users. What to keep in mind is that I already have counts for the ...
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1answer
2k views

How to decide the number of trees parameter for Random Forest algorithm in PySpark MLlib?

I am working on Random Forest algorithm in PySpark MLlib and have a doubt regarding the ...
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1answer
134 views

What regressors are recommended with text modeling?

For the sake of my own exploration, I am working on a sales prediction project. I am using text extracted from a set of books to build a predictive model. With scikit learn, I have created a Tfidf, ...
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3answers
3k views

Best regression model to use for sales prediction

I have the following variables along with sales data going back a few years: date # simple date, can be split in year, month etc shipping_time (0-6 weeks) # 0 weeks means in stock, more weeks means ...
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169 views

Confidence range for individual prediction from multiple regression

I've built a multivariate regression model for predicting the price of an item given a couple of other factors about that item - age, condition, etc. So, given values for age and condition I can ...
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3answers
5k views

Export weights (formula) from Random Forest Regressor in Scikit-Learn

I trained a prediction model with Scikit Learn in Python (Random Forest Regressor) and I want to extract somehow the weights of each feature to create an excel tool for manual prediction. The only ...
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1answer
2k views

How to select regression algorithm for noisy (scattered) data? [closed]

I am going to do regression analysis with multiple variables. In my data I have n = 23 features and m = 13000 training examples. Here is the plot of my training data (area of houses against price): ...
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1answer
32 views

Predicting when a partition in Oracle database will be archived

We have an Oracle database in which the main table "A1" is partitioned by the hour of insertion of the row. A row once inserted, may be updated depending upon data in 6 other tables (B,C,D,E,F,G) in ...
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2answers
1k views

Improve a regression model and feature selection

I am working on Azure ML Studio and try to create a regression model to predict a numerical value. I will try to describe my features and what I have done until now. My data with about 3 million rows ...
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0answers
50 views

Has anyone defined a spline function (i.e. defineFuction) in PMML?

Has anyone defined a spline function (i.e. defineFuction) in PMML? There are quite a few parameters that need to be defined, with a fairly lengthy math. For example, for a predictor with a simple 3-...
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3answers
1k views

Can regression trees predict continuously?

Suppose I have a smooth function like $f(x, y) = x^2+y^2$. I have a training set $D \subsetneq \{((x, y), f(x,y)) | (x,y) \in \mathbb{R}^2\}$ and, of course, I don't know $f$ although I can evaluate $...
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75 views

Regression problem - too complex for gradient descent

I try to predict temperatures values as function of time and different parameters. The temperature curve look like a "ramp" with some "gauss peaks" on regular intervals. So, I try to build a ...
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2answers
258 views

Random Forest Regression. How to represent really long list of categories for processing

I'm trying to build a model to solve a regression task. Simplified, the data look like: ...
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1answer
843 views

Combining Linear Regression and Time Series

Does anyone know of a predictive model that can combine the linear regression model and time series model? I have some data about some products. The data has two parts, some attributes about the ...
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1answer
12k views

Categorical and ordinal feature data representation in regression analysis? [closed]

I am trying to fully understand difference between categorical and ordinal data when doing regression analysis. For now, what is clear: Categorical feature and data example: Color: red, white, black ...
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1answer
43 views

Regression: how to interpret different linear relations?

I have three datasets, let's call them X and Y1 and Y2. A scatterplot is produced out of ...
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153 views

Regression: Scatterplot with low R squared and high p-values

Based on three datasets, I have produced the scatterplot below in Python: I am trying to fit a line on each dataset, but when I check the metrics this is what I get: Set 1 (red): R squared=0.002,...
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2answers
457 views

Which Spark MLlib regression algorithm is suitable for numeric predictions based on non-numeric features?

I am working on Spark MLlib and have a project where I have to make predictions for numeric data based on non-numeric features. I am a bit confused about which <...