Questions tagged [predictive-modeling]
Statistical techniques used for predicting outcomes.
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Why XGBoost regressor predicts behavior but not the amplitude?
I am very new to machine learning and I am trying to use XGBoostRegressor for my machine learning model (it has to do with physical modeling).
I found out that it works very well for predicting the ...
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1answer
19 views
What method is recommended after outliers removal?
I have a data of mice reaction times. In every session, there are some trials in which the mouse "decides of a break" and responds after a long time to these specific trials.
I was thinking of ...
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Common text data sets in form of panel data [migrated]
I want to test machine learning tasks on time-divided textual data set. For this purpose, I want to use a common text data set which is already validated and "good" for use. I already found a Web of ...
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1answer
22 views
Classification - Divide the interval (0 - 1] to lets say 100 classes and use each class to make a calculation
class-1 represents 0.01, class-i represents 0.01*i, class-100 represents 1.00.
Thus, when the classifier predicts the class-y and it should have predicted class-(y+1) there is a small error so we can ...
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2answers
27 views
Does the predict function in machine learning understand categorical data
I understand that before feature engineering one has to split the dataset into train and test data, so as to avoid bias in the analysis. I also understand that the machine learning model does not ...
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13 views
Ho do I model spatial-temporal data with python?
Can someone get me started with the following:
I have data of rare events including time and location. I want to predict future events based on past events occurring in a particular region and its ...
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22 views
Pre-training model with existing seasonal data for new dataset with maximum limit
I apologise if this is a simple one, I'm not sure if this is not possible or if I'm just not using the right keywords to find the answer;
Say I've got a pizza store, I've been able to successfully ...
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1answer
37 views
Can I apply survival analysis to predict if a user will revisit the website?
I have one business problem in hand which is to predict if a user will revisit the website or not within 6 months. I need to majorly understand what are the factors which make the user return and also ...
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1answer
32 views
How do I use multilevel regression models?
I have crime event data rows:
dayofweek1, region1, hour1, crimetype1
dayofweek2, region2, hour2, crimetype2 ...
and I want to use them as factors to model crime ...
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1answer
37 views
Doing predictive modeling on predicted value
It's a project that I'm working on. Here are the steps I took:
I want to make a recommendation service based on the customer data. I first used a collaborative filtering method to get the recommended ...
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2answers
25 views
Is using cross validation on your entire dataset acceptable when dealing with a small sample size
Normally my practice includes using k-folds cross validation on a subset of my dataset and keep a final test set.
When dealing with an exceptionally small dataset, is using cross validation on the ...
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16 views
How to apply transfer learning on a regression problem?
I am working on predicting mechanical failures and I have trained a model to predict when a component will fail on what type of machine. I would like to now use this prediction model to predict the ...
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1answer
29 views
Deep model ensemble giving different results
I am making an ensemble of deep models for solving a classification problem. The initial weights follow the default distribution of keras layers. Each time I run ...
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12 views
Does the type of y value affect the prediction power of model?
I am using the sunlight intensity time series data(X) to predict plant height(Y) in different locations using CNN model in Keras.
I am wondering if I change the group Y values into 2 categories: High ...
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2answers
143 views
Suggestion for stacked modelling in machine learning
I have built several models on the training dataset and i am not happy with the results and I wish to club them all together and generate a new model, so here is my idea as i already have the results ...
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25 views
Rescale prediction to correct dispersion due to correlation between response and residuals in Random Forrest Regression
I am using Random Forest Regression and I observe a strong positive correlation between the residuals ($\hat{u}$) and the response variable ($y$) which lead to a dispersion : predictions are ...
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14 views
Optimal practices to group data by Customer ID for churn prediction
Here's a quite common problem and I read a couple of questions/answers on it, however I still having my doubts about what are the best practices for grouping data by Customer ID for churn prediction.
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1answer
24 views
Time Series segmentation
I have a time series graph that is segmented into a few parts based on the maintenance day. You can think of it like vertical lines appearing out of the x axis which symbolize maintenance at the date. ...
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1answer
28 views
Predicting churn - deal with missing dates in time series and improve modelling result
This is the follow up question for General approach on time series for customer retention/churn in retail.
I have a time series of data in the following form:
...
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27 views
How exactly do probability distributions help modeling/making decisions?
I am an elementary/wanna-be statistician/data scientist from South Korea. I have been studying a variety of theories of mathematical statistics and different probability distributions. (I apologize ...
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Data Analysis on Data From Analytical Techniques
We have a set of data that are generated from analytical methods. In other words, data regarding the behavior of a system from different aeronautics and aerodynamics equations. We want to perform data ...
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How to deal with similar feature values but each indicates to a different information?
If I have a feature with replicated values but each of these values indicates a different piece of information.
example: feature 'street name' with value 'A' which some of these 'A's are for Boston ...
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13 views
Is this a reasonable way to deal with known input data uncertainty for logistic regression predictions?
Suppose I want to use a logistic regression model to predict the class of N objects. Further, suppose the prediction is time sensitive: I need the prediction for each object on Day 1, but the value of ...
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1answer
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Is it possible to use an array of graph coordinates as an input variable?
Say I have 1000 graphs that shows sales every year for the last 10 years for 1000 different companies. And say each of those graphs belong to either domestic countries or foreign countries.
Is it ...
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2answers
49 views
LSTM to predict Sin(x) from x
Hi I want to pass a series of values x1, x2... as input to the model to predict y1 = sin(x1), y2 = sin(x2)...
-I created dataset: x=[0.1,0.2,...] and y=[sin(0.1),sin(0.2),...]
-I normalize x in [0,1]...
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1answer
25 views
How do I deal with changing values in a categorical variable when I am aggregating customer records
My requirement is to build a model to predict if a new customer will return to their website. I need to analyze what drives customer repeat for both new and returning customers. The only information ...
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1answer
36 views
Predict correct answer among ten answers for a given question
I have a case study to solve where I am given a dataset of questions and its answers, there are ten answers for a particular question.
It's a classification problem where correct answer is having <...
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2answers
48 views
What is the difference between a data-driven model and an empirical model?
Are they the same?
Empirical models, per Wikipedia, are
any kind of (computer) modelling based on empirical observations rather than on mathematically describable relationships of the system ...
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0answers
19 views
What is the best approach to train a multi-category regression model?
What is the best approach to train a multi-category regression model (using XBoost decision trees ensemble)? What are the ups and downs of each one? For example, if I want to train a model to predict ...
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1answer
22 views
Minimum Possible Test MSE
I have a little confusion.
What follows is from Introduction to Statistical Learning (2013) by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.
My understanding of what is going ...
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1answer
31 views
How to deploy machine learning models as a chrome extension?
I have trained a stance detection model using SVMs. Wanted to know how can I deploy this as a chrome extensions. I do understand that the question is a bit broad but any links, suggestions etc. will ...
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1answer
34 views
How to approach data prediction problem
I'm new to ML and data science. I would really like high level advice how to approach the following problem. I need to predict if an engine will fail, what I've is a sensor that give a certain value ...
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Increase accuracy of occupancy prediction?
I have a project that's aimed to predict the amount of occupants at my local gym given the date and weather.
Here's my Kaggle kernel
I have two datasets, occupants on a given hour and weather on a ...
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8 views
pattern recognition tool
From what i've seen while searching google and the site this is most likely way simpler than what normally get's asked but i've not been able to find anything that could help me with it.
What i'm ...
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1answer
126 views
Machine learning method to predict event date
Let's say I have a big dataset consisting of variables including but not limited to the start/end date of loans, their notional amount, a loan prepayment indicator etc.
My goal is to create a model ...
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1answer
21 views
Tree based method are robust against low probability feature space zones when using ML general interpretability methods?
I have this intuition but I'm not able to verify it.
There are a lot of techniques to understand the effect of single features in ML models. Some take inspiration from counterfactual frameworks, like ...
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1answer
39 views
Will historical data lead to target leakage?
I'm bulding a employee churn model. I've employee data from 2016 to 2019 (of people who stayed/left the company), my goal is to train using data from 2016 to 2018 and predict on 2019.
Since there's ...
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SRGAN: How to adapt the model to the input image?
I wrote and trained my own SRGAN: so I obtained a generator’s model that takes 32x32 images as input and gives their improved 128x128 version as output…
However, the end users of my Android app will ...
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1answer
47 views
How to restructure my dataset for interpretability without losing performance?
What I am doing:
I am predicting product ratings using boosted trees (XGBoost) with a dataset in this format:
What I want to do:
I want to use SHAP TreeExplainer to interpret each prediction my ...
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2answers
48 views
Dealing with NaN for predictive models
I have data set that has data for patients:
Arrival_Date : is when the patient has arrived
Seen_By_Nurse : is number of minutes patient take to be seen by nurse since arrival
when value is NaN it ...
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0answers
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Beating Roulette with Neural Networks, YoloV3, and PyTorch
Background:
I am in my last semester of electrical engineering, and I am working on my senior design project. The senior design project is a two-semester design project in which students outline, or ...
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1answer
22 views
Will the performance of my NER model improve?
I am training a spacy model from scratch by creating a dataset of my own with format spacy needs it to be in, the model is an NER model and the entity i am trying to recognize is Food items. I have ...
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How to handle a data set with large number (about 75%) of binary variables?
I am doing a research right now and want to classify (predict) churns of costumers using machine learning. My data set consists of about 500,000 observations with 20 variables: 15 are binary, 2 ...
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2answers
30 views
Time series modelling
I have daily data for 2.5 years , but with more data points as 0, so when i excluded them in the cases which seems to be invalid. Can i use any other model than models used in time series or should i ...
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2answers
48 views
Traditional Predictive Analytics vs Machine Learning Methods
What is the difference between traditional predictive analytics done using statistics and its tools and, one using machine learning and deep learning?
How are we leveraging machine learning and deep ...
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2answers
41 views
Model should predict the same value every time for the same input
I have used a random forest model for prediction of prices. Should the model be predictable in its behavior? By this, I mean that I'm not changing the model and the input, Will the predicted value ...
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1answer
16 views
LightGBM choice of evaluation metric
I have past data of a large number of people who applied for a loan and their movement through 8 different stages, from start of application to loan being paid out.
I am trying to build a model that ...
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1answer
59 views
Precision Vs Recall Curve analysis
I have the following averaged 𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛−𝑟𝑒𝑐𝑎𝑙𝑙 curves with 4 models. Which one is the best?
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Hierarchical prediction
Suppose the problem is the following: there is, say, binary target variable $x$, and real-valued target variable $y$, which is only relevant if $x = 1$. What is the best way to train a model to ...
