Questions tagged [predictive-modeling]
Statistical techniques used for predicting outcomes.
930
questions
3
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1answer
94 views
Why is oversampling outperforming class weight?
I have a dataset that is highly imbalanced. One class has 412 (class 0) samples while the other has 67215 (class 1) samples. For its classification, I am using MLP. When I use class weight of 165 for ...
0
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0answers
9 views
List of platforms or interfaces that get humans to label datasets for machine learning training purposes?
Due to it being a new and fast-changing space, it's difficult to find reliable information on the different platforms/companies/services available to outsource the labelling of training datasets.
...
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2answers
122 views
Compare Classification Performance in Datasets drawn from Different Populations
I've read some classics about comparison of ML Algorithms i.e.
...
0
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0answers
9 views
Multi target model with only one input variable?
I am about to develop a manual model relating different input and output features regarding the operation of a powerplant with its power generation. Some features have a linear tendency with energy, ...
0
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0answers
23 views
How could you predict customer churn using transactions date?
I am new to machine learning and I would like to predict churn using dates of transactions. I tried to prepare my data and I couldn't obtain good results.
I would like to predict unique Customers, ...
0
votes
0answers
12 views
How to model a decimal response between 0 to 1 with a GLM in R
I am trying to model a response variable which is a proportion (so a response between 0 and 1, see picture for distribution).
Ideally I would like to model it without using the actual counts, so as a ...
0
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0answers
12 views
Measuring the bias of a machine learning model
How can we measure the bias of a machine learning model? Can we determine it by just calculating its performance estimates difference on the train data and test data? For example, if a model SVM ...
1
vote
1answer
68 views
gradient descent diverges extremely
I have manually created a random data set around some mean value and I have tried to use gradient descent linear regression to predict this simple mean value.
I have done exactly like in the manual ...
0
votes
1answer
28 views
Dimensionality reduction and prediction when all columns have approximately same variance
I have a dataset of 25 columns where the goal is to predict the value of the 25th column based on the previous 24 columns.
The dataset is quite big that's why I initially thought to proceed with PCA ...
1
vote
1answer
20 views
Ngram based Langauge Models learned using an Encoder-Decoder Model
I have been going through a Ngram based Langauge Model learned using an Encoder-Decoder Model for Email smart compose.
The program output only 1 prediction for given input.
I want to know how to ...
1
vote
0answers
36 views
“Smearing” probabilities or how to handle imprecise locations for canonically classification-type problems
I am trying to predict failures at different nodes on a line. Each node has different weather features and hardware/configuration features. For a little under half of the historical failures I have, I ...
1
vote
0answers
46 views
How to incorporate the uncertainty of the model coefficients in the prediction interval of a multiple linear regression
I'm dealing with the modeling of small experimental data sets. As most experimental work does not generate thousands of samples, but rather a handful, I need to be inventive in how to deal with this ...
1
vote
1answer
139 views
Brownian motion in models for virus spread?
Was reading a Washington Post article "Why outbreaks like coronavirus
spread exponentially, and how to flatten the curve” and it looked like they were using Brownian Motion.
(Can't directly link the ...
0
votes
1answer
62 views
Model to predict coronavirus (covid19) spread [closed]
im new in data sience and machine learning but i have some mathematical and statistics backgroud. I really just want some information about models (like papers or raw models). So if you have any ...
1
vote
1answer
73 views
TF Keras Text Processing - Classification Model
I'm trying to put together a script that classifies comments into either adequate or inadequate. I put a question up here earlier with all my code, but I think I've isolated the problem down into the ...
0
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1answer
24 views
1
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0answers
48 views
Hedge fund rank on their returns or rating predictions modeling problem
Problem:
Hi, I m a new machine learning practitioner. I have a dataset about hedge funds. It contains monthly hedge fund returns and some financial metrics. I calculated metrics for every month from ...
0
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0answers
20 views
Forecasting sales during time of epidemic
As we are going through a tough time because of the Coronavirus epidemic, is it possible to somehow include this affect of this in predicting sales as a time-series for next few weeks?
I am new to ...
0
votes
1answer
31 views
Meaningful predictive analytics for small (n=114) dataset with just 1 explanatory variable and 1 response variable?
I am given an Excel pivot table that aggregates data from a somewhat sizable data source (a database table with 1.9m records and another of about 490k). The data within the Excel file consists of 3 ...
0
votes
1answer
35 views
What model do I use to predict a regression problem with timeseries data
Overall Goal
To predict how much reagent "A" I started with in a reaction.
Data:
To predict this I have timeseries data of reagent "B". For each time step a measurement of reagent "B" is taken (the ...
0
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0answers
14 views
Predicting future of power consumption in repeating manufacturing process
I have this situation. We are tracking the power consumption of an industrial machine and by looking at the power consumption (in watt) we're trying to predict whenever something will break resulting ...
0
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0answers
9 views
What are and how can I unserstand/process geo levels id from this dataset?
I am using the dataset from this driven data competition: https://www.drivendata.org/competitions/57/nepal-earthquake/data/
There are three features (geo_level_id_1, geo_level_id_2, geo_level_id_3) ...
0
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0answers
16 views
HR Machine Learning: Treating/ Standardizing Part Time Employee Sums To Their Full Time Equivalents in Attrition Modeling
My data set consists of a subset of employees. Each employee has general HR information (typical standard hours, department, site, etc) along with punch card data which gives a clear picture of the ...
2
votes
1answer
23 views
Ideal strategy for multi variable regression attempting to maximize the target
I am trying to implement machine learning for the following data
Data Input
What I am trying to achieve is to keep the ad bid & cost per sale as low as possible while increasing sales.
This is ...
0
votes
1answer
20 views
Using a past time series to predict how a present time series will pan out?
Let's say that I have past data indicating how some time series panned out. Now I also have the beginnings of a new time series that I expect to pan out in a similar trend to the old one.
What are ...
4
votes
2answers
110 views
Determine statistically whether new product cannibalise old product by using data
Assume that $A$ is a cab company which offers online cab booking through their standard account.
Recently, the company launched a pre-paid premium account with features such as discounted rides,...
0
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0answers
19 views
Clustering a dataset and creating a model per each cluster
I was wondering if it makes sense to cluster a dataset to find closely related data points and train a binary classification model for each of this clusters as they would be minidatasets. I'll ...
0
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0answers
16 views
Trouble understanding how I could use multivariate time series to predict when an error will occur?
First off, I have very limited knowledge statistics-wise and am more of a coder. I was thrown into a large scale project and could use some guidance.
I have a large multivariate time series dataset ...
3
votes
0answers
20 views
Serializing a trained classification model into a set of actionable insights
I'm looking for ways to convert a trained classification model into a list of insights based on the resulting parameters of the model.
To make an example, let's assume we trained a decision tree to ...
0
votes
1answer
19 views
I want to detect similar meaning in sentence “in my final year web based system” [closed]
When students submit a topic for his/her final year research, the system should be able to detect that this topic was carried on by some student or already exists.
How can I be able to do it? If its ...
2
votes
0answers
65 views
RUL prediction without failures in historical data
I have faced in the past some problems of predictive maintenance where I had historical sensor data with failures. With this kind of dataset, you can calculate the RUL (Remaining Useful Life) and ...
1
vote
0answers
24 views
Plotting the decision boundary of different combination of 2 features from amongst a large number of features
How to plot the decision boundary of different combinations of 2 features from 107 feature data set?
...
0
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0answers
12 views
How to set anomaly threshold depending of predictive model accuracy
Say I have a variable with a standard deviation STD
I have a predictive model to predict variable. The model accuracy is 80%
An anomaly is raised if difference (predicted_value - actual value) > ...
0
votes
1answer
20 views
How do I build a model to predict which service a customer will use on an app?
There's an app with over 50 services. I have the data on the type of service a specific customer (they have a unique customer number) does on the app, the date, location, time, duration on a service ...
0
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0answers
767 views
nlp method to define/predict labels from text
I have a hundreds of invoices from company A to company B. Structure of every invoice is different, but in every invoice I have typical labels like date, company title, company id, amount etc.
I ...
5
votes
1answer
28 views
Identifying and Accounting for trend/seasonality in Predictor Variables
I'm currently working with a dataset that has been collected over several years, and I suspect my predictor variables are changing over time for their predictive power.
I could go back year by year ...
1
vote
0answers
39 views
Model-independent measures for feature importance given highly correlated features
I am currently working on a research project where the central question is which features drive the prediction of different models. The main issue is, that there is high (multi-)collinearity among ...
2
votes
1answer
25 views
How can you adjust a prediction based on features in the future being different than predicted?
I have a model that takes mostly cumulative data, and makes a prediction. It's not baseball, but I'm using this as a pretty accurate analogy. You put in all the totals so far, and it make a prediction ...
2
votes
2answers
125 views
How to train my model efficiently?
I am new to ML and have been reading online about training bottlenecks when there are frequent updates to data.
Let's say I have a built a model based on a dataset of 10M records.
Now, in another 2 ...
3
votes
2answers
46 views
What is an appropriate approach to sampling for probability of default using a classification model?
If we have a loan book and want to train the data to predict the probability of default, what is an appropriate way to sample the historical data to train the model, given that each account is open ...
0
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0answers
17 views
Matlab - Financial Modeling, Linear Regression with Prior
Am trying to implement this equation from the book Doing Data Science Straight Talk from the frontline, In chapter 6, page 161, equation below:
From what i can tell it is pretty much an enchanced ...
1
vote
0answers
14 views
Clustering and producing final results to find next best customer to target(Ranked)
I have a problem where I need to cluster customer data that has all possible attributes to identify the next potential customer who can succeed the last customer in terms of buying a certain product. ...
2
votes
4answers
101 views
Machine learning approach for predicting set members
Say I have a large training dataset containing sets of 40 items each, and each item in the set is unique (so every training input is a set $S=\{i_1, i_2, ..., i_{40}\}$), and there are more than 40 ...
1
vote
1answer
29 views
Predicting the next occurrence based on binary
I have no experience in statistics or machine learning. I have a True/False binary array describing occupation of open public spaces
...
2
votes
0answers
21 views
GuassianNB partial fit not working properly
I'm trying to make a partial fitting with GuassianNB here's small snippet of my code
...
3
votes
0answers
48 views
How can I improve the accuracy of my model? (Cab Cancellation Prediction)
I am trying to predict based on several parameters like trip type, car type, source of booking, start time, lead time (start- book) and a few other params whether or not a customer will cancel. From ...
2
votes
1answer
40 views
Prediction for Current month based on last month's Labels
I have monthly data of loan installment repayment. The data contains basic features like salary,age,gender, credit score etc.
Along with above features, i have data for last 6 installment failure/...
2
votes
2answers
411 views
Modelling data with Machine learning without a target variable
I want to understand the required steps that need to be taken into account while handling a dataset that does not have a target variable.
I can do machine learning on top of a labeled dataset having ...
4
votes
1answer
388 views
Calculate confidence score of a neural network prediction
I am using a deep neural network model to make predictions. My problem is a classification(binary) problem. I wish to calculate the confidence score of each prediction. As of now, I use ...
1
vote
0answers
25 views
Calculate marginal probability distributions of a dataset
I have a dataset with 'n' features and a label(binary) corresponding each entry. I am using a predicitive model to predict these labels using those 'n' features. Now, I wish to know the marginal ...
