Questions tagged [predictive-modeling]
Statistical techniques used for predicting outcomes.
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31 views
Sports prediction using machine learning
I am trying to predict soccer scores using past results. The dataset I have only consists of the home team, the away team, goals scored by the home team and goals scored by the away team in each match....
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0answers
11 views
Job Recommendation System
I am building a Job Recommendation System where I have Student Data for different subjects in Machine Learning(Data Viz, Python, Statistics, etc) and their skills from the resume. Need to Recommend ...
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1answer
17 views
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1answer
15 views
Using LSTM's on Multivariate Input AND Multivariate Output
I have a very small dataset, only about 40 rows, that has historical usage data for a few categories (roughly 20). I strongly suspect that these categories are dependent in a partial-zero-sum-game ...
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6 views
Specific data formatting techniques for discontiguous time series?
I'm facing a predicting problem for food alerts. The goal is to predict the variables of the most probable alert in the next x days (also any information I could get about future alerts is really ...
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11 views
Anomaly Detection: Model Creation & Implementation
I'm trying to determine the best approach to an anomaly detection problem. Particularly around setting up the data, building the models, and leveraging the models to identify important information.
...
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1answer
37 views
Machine Learning in real time
I am a newbie in ML world, but very curious and enthusiastic about it. Have gone through articles and some hands-on too. Still got a silly doubt.
In sample datasets (like Iris or diabetes or breast ...
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6 views
Mapping 4 Dimensional array to predicted output text
Iv been studying machine learning but im struggling with some concepts and cant seem to find particular answers to the question of how theoretical data is mapped into non classification categories.
...
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1answer
38 views
ML - Service Desk classification
I'm trying to explore an use-case in ML but stuck at a point. May i please request your advise please.
Have a service desk web application for logging tickets, which is essentially a form having ...
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0answers
10 views
Bayesian Neural net with non probibalistic Data?
Is it possible to construct a Bayesian Neural Network without Probability Distributions as dependent Variable for purpose of predictive modeling?
I mean, if id like to Infer on a Specific Value, like ...
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0answers
19 views
Excluding goal column scaling for LSTM not working giving invalidarguement error [closed]
I am trying out a simple LSTM experiment. Basically the goal is to predict final stage as the prediction value. I am following the standard flow of first plotting, then scaling, the reframe, next ...
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1answer
17 views
How to do Predictive Modeling for Different Companies
There is Company X
Company X wants to predict if its opportunities will Win or Lose
I trained my model based on the data of company X
and did the prediction of new opportunities
Now Company Y and ...
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2answers
24 views
model to predict annual outcome based on previous years data
I have below datasets for two years each holding about 10.000 records. Every week a new report is generated that shows the performance for the current or any previous month. Therefore a more recent ...
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0answers
40 views
Feature importance and probability score out of Decision Trees
We all know that Decision trees are super interpretable but one thing that I am not able to understand is the mathematics behind it. So, I have three questions here :
How do Decision tree and Radom ...
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0answers
19 views
How to improve a model with a high cross validation score yet with low accuracy on unseen data?
I have a model that is based on an experiment collected on 100 subjects. We are testing the model as follows:
Record raw data from the subjects
For each subject, compute the feature from the raw data ...
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1answer
21 views
How can we show that one model might have higher accuracy than another model but at the same time lower AUC?
Assume that we have two classification models M1 and M2 that are evaluated on five test instances. How to show with an example that M1 can have a higher accuracy than M2, while at the same time M2 has a ...
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0answers
20 views
Label construction for predictive maintenance
I am trying to do a binary classification related to predictive maintenance. The question I address is "What is the probability that the asset will fail in the next X units of time?" There is a guide ...
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0answers
8 views
Predicting if an Aribnb listing will be sold out on certain dates
The use case:
A user is searching for a listing on Airbnb with specific dates.
I need to predict the probability that the listing will be sold out soon. Also, if possible, when it would be sold out (...
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0answers
23 views
How to figure out if the problem is solvable by any machine learning algorithm?
I am trying to solve a problem in the domain of the audiology, to predict the value of an audio gain in dB. My data is made of:
10,000 training samples
1,000 validation samples
10 features
The ...
1
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1answer
34 views
Predict the loss amount for insurance policies using the historical trends and features?
Anyone who has worked with insurance policy datasets, please guide me to an appropriate dataset for this problem .
Also, what is this 'loss amount' and what model will be appropriate for it?
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0answers
39 views
how to perform anomaly detection on industrial machine's sensor data?
I've two types of datasets, training(when machine working under normal conditions without any fault) with multiple sensor data(features) and test dataset(contains some of anomalous data). I want to ...
1
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1answer
32 views
How to merge personalized models together
Let's say I'm building an app like Uber and I want to predict the user's most likely destination based on the user's past history, current latitude-longitude, and current date and time.
We have ...
4
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2answers
59 views
Can we predict when an event will occur in the future from time series data?
I would like to predict a few possible times when a particular event may occur. For instance, I have the daily activity data of a person that consists of what the person doing and when over a period ...
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1answer
65 views
How to calculate prediction error in a LSTM keras
I have an LSTM which I have constructed and run in keras using python. I use this model to predict $n$ points into the future for a time series forecasting problem.
When I use a method such as ...
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0answers
18 views
Multivariate forecasting with LSTM input output data shape
I have to predict the number of sales for 215 products in 60 different shops, training on the sales of 31 months(973 days) and validating on 2 months(61 days).
I have created 4 dataframes.
train_x: ...
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1answer
20 views
Historical weather data with machine learning? [closed]
My company gave me a task to build some weather forecasting. I have now historical weather data for 10 years (temperature, precipitation in mm, humidity and etc. more than 30 features total). We need ...
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0answers
6 views
With two deep learning models, how do I perform Bayesian Model Averaging for better prediction on a test set?
Given two deep learning models that can predict on a test set, what I want to do is use BMA (Bayesian Model Averaging) to average the models to better predict?
What exactly is the procedure for this?...
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0answers
11 views
Is employee attrition regression or classification problem?
I'm currently working on employee attrition project. I want to predict the attrition rate of day-n. So, I want to give a report such that probability of an employee to stay in company at day-m, day-m+...
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2answers
27 views
When to build separate models
I'm pretty new to predictive modeling, but am interested in generating predictions for credit card account spend. These are existing accounts.
The data I have available to me is Card Type (i.e. ...
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0answers
8 views
add a constraint to a DQN
I have a DQN (with 5 state variables) but I want to add a constraint to it such as (p<10), which p is a parameter which is not one of the state variables. However, there is a hide relation between ...
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0answers
4 views
How to attribute variance to an input parameter?
Some data
Maybe this is easiest to explain by going straight with the data. Here is how much money Bob has at the end of each day.
...
1
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1answer
28 views
RNN package and problems with “Predictr”
I have two questions about how to use R's RNN package, specifically the trainr and predictr functions.
Let's suppose I have a time series of 4000 steps for 5 different variables.
How should this be ...
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1answer
25 views
How to train a model to predict a time window than an event will occur on a website
I have a list of historical timestamps of when a specific event occurred on a website. Currently the timestamp represents a 30 minute window that the event happened within. I am looking to train a ...
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2answers
42 views
How to find out bad images?
I have a task to find out bad visuals from given video.
Let's define bad images in the video as per the human brain -:
...
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1answer
21 views
Can random forest algorithm provide customer churn prediction probability at each customer instead at class level?
I have customer training data set from telecom industry along with its test data set containing churn values 0 & 1 for each customer. I also have customer data set whose churn value is to be ...
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1answer
15 views
During a regression task, I am getting low R^2 values, but elementwise difference between test set and prediction values is huge
I am doing a random forest regression on my dataset (which has abut 15 input features and 1 target feature). I am getting a decently low R^2 of <1 for both the train and test sets (please do let me ...
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0answers
9 views
What techniques or approaches can identify if nearby labeled data have been sampled frequently enough for good inference?
Beginnerish question, and I've got a whacky thought experiment / application to demonstrate the problem rather than try to explain it abstractly or academically, which I can't figure out how to do.
...
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0answers
27 views
What is the use of coefficient in in Machine Learning
What is the meaning of coefficient values in Machine Learning. After I print
model.print_summary()
It shows, coefficient values of for each column. But I really ...
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0answers
18 views
How to feed my categorical data into my model?
This may be a basic question, I have a categorical data and I want to feed this into my machine learning model. my ML model accepts only numerical data. What is the correct way to convert this ...
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2answers
75 views
What is the difference between SVM and logistic regression?
While reading the book by Aurelien Geron, I noticed that both logistic regression and SVM predict classes in exactly the same way, so I suspect there must be something that I am missing. In the ...
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0answers
12 views
How to get the survival duration prediction for each individual in the data by using the Kaplan-Meier method?
I am trying to learn how to use the Kaplan-Meier survival estimator model in the lifelines package. The documentation says that the KaplanMeierFitter.fit function ...
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0answers
13 views
Why GP (Gaussian Process) works?
Actually I read through some papers about GP(google the stanford university and oxford university lecture pdf and read)
I knew the procedure to do it with detail to choose the kernel and test and the ...
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0answers
34 views
Forecasting/predicting techniques for qualitative data?
I have a food alert dataset composed of nominal qualitative variables, such as type of alert, country of origin, action taken, etc. as well as the date on which the alert was recorded.
What ...
1
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1answer
22 views
How to predict unknown(hidden) value by incomplete value or partly recorded value
Let me make it clear by make an example:
Suppose I knew a person's cost each month for 3 years like:
2016Jan : $2500
2016Feb : $4000
2016Mar : $3500
...
Just according to this, can I ...
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2answers
28 views
Finding interaction
How do you find the interaction between a continuous and a categorical variable? I have tried using ggPredict but it doesn't seem to work if there are more levels.
...
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2answers
67 views
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1answer
39 views
What could be a dataset in which the presence of an outlier dramatically affects the performance of Ordinary Least Squares (OLS) regression?
I am tasked with giving an example of a dataset in which the presence of an outlier dramatically affects the performance of
Ordinary Least Squares (OLS) regression. I've searched and searched the web ...
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0answers
5 views
Which Keras model, if any, is best for this unusual (K,N)-multinomial predictive task?
Say I have a bunch of images that were classified by $N$ people. Each person classified each image into one of $K$ categories. For each image, the votes for each category are then summed up.
As a ...
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0answers
10 views
Why is my regression predictions values variance different from real values variance
I am modeling a physical process using a regression(XGBoost).
I'm looking for ways improving my model, have tried different things without success.
Decided to get a better intuition on where my model ...
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1answer
27 views
Prediction: plugin a corelation table (neuron) into a Time-Series Neuron in Keras/ TF
i am adding more details
I have a time series of Babies (1,2,3) showing how many problem they have each week (Born week 1 to week 80) and in which organ (14 organ).
There is a separate numeric time-...
