Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

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8 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) > ...
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1answer
12 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 ...
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17 views

Different length of data samples at the input and in the model [closed]

Let's assume that we have a 24-hour ECG signal divided into 4-minute intervals and we calculate HRV characteristics based on this 4-minute signal. Is it possible to predict on this model, but the ...
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15 views

How to predict number of “stops” for coming weeks using previous week's data and weather data?

I'm getting confused as how to proceed for this problem: I need to predict the amount of stops (the amount of a driver stopping at an address to deliver a package) based on previous' weeks data and ...
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30 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 ...
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1answer
25 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 ...
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17 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 ...
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1answer
21 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 ...
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2answers
100 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 ...
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2answers
36 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 ...
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12 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 ...
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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. ...
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4answers
53 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 ...
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1answer
26 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 ...
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0answers
15 views

GuassinaNB parital fit not working properly

I'm trying to make a partial fitting with GuassianNB here's small snippet of my code ...
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0answers
31 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 ...
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1answer
23 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/...
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2answers
92 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 ...
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1answer
126 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 ...
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13 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 ...
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4answers
1k views

In industry, what type of new data science algorithms does one develop?

I've seen several job descriptions for data science which include developing a novel algorithm to be a part of production environments. Can you give some input of what could be meant here exactly? ...
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1answer
25 views

Modifying a distribution by adding in samples incrementally

I would like to calculate the distribution (e.g., Gaussian) of a set of samples. However, I would also like to see how the distribution changes as I fit the samples into the distribution ...
2
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1answer
43 views

Machine learning solution approach to match loan repayments

I'm relatively new to the AI/ML space, but come from a programming background. The problem: I have a dataset of users transactions who have taken short-term loans from a single loan provider and I ...
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21 views

Improving a simple trig model

I have some data which I know is well approximated as a trig function, and I can fit it with scipy.optimize.curve_fit as follows: ...
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2answers
36 views

To find lookalike customers for Digital media targeting [closed]

I want to develop a model for digital marketing team. We have some set of ideal customers to whom we to send our promotions and have been converted. Now we want to pick past such cases and want to ...
2
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1answer
34 views

Find Net Reclassification Improvement/Index metric using Python

I am working on a binary classification problem with ~5k records and class proportion of 33:67. I have 60 features/variables in my dataset and finally I have come to about 10 variables based on ...
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1answer
33 views

How to evaluate performance of a new feature in a model?

I am working on a binary classification where I have 4712 records with Label 1 being 1554 records and Label 0 being 3558 records. When I tried multiple models based on 6,7 and 8 features, I see the ...
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1answer
28 views

Why results of statsmodel logreg is different from scikit-learn logreg?

I am trying to do a binary classification. I have only 6 input variables and one output variables. Label 1 is 1554 records and Label 0 is 3558 records. As you can see below, the metrics that I get ...
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4answers
361 views

How to impute Missing values not the usual way?

I have a dataset of 4712 records working on binary classification. Label 1 is 33% and Label 0 is 67%. I can't drop records because my sample is already small. Because there are few columns which has ...
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0answers
19 views

SVM C vs gamma hyper tuning

While running SVC(), how we can hyper tune C vs gamma combination? I could see changes in C and gamma are impacting the accuracy differently. Also what i understand about C and gamma are : 1) C is ...
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2answers
43 views

Kernel selections in SVM

I want to understand the kernel selection rationale in SVM. Some basic things that i understand is if data is linear then we must go for linear kernel and if it is non-linear then others. But ...
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1answer
27 views

Time Series Classification for loan data

I have multiple columns for loan installment repayment. As there is a field for month of repayment. I want to predict if the customer is going to pay next month installment or not. As I have ...
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2answers
65 views

Machine learning model bundled with a library vs. an API

I am thinking to "deploy" a machine learning model (in pickle it is sized 3 megabytes) and after discussing with my developer colleagues, they said it would be better if the model is packed as a ...
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0answers
26 views

Omnibus and R square improvements for OLS model

Checking on this community if any one can help on below problem posted by me on stats.stackexchange. https://stats.stackexchange.com/q/441653/266047 Detailed question is as below: ...
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1answer
28 views

Why and how to match variables in logistic regression?

I have a dataset of ~4.7K records focused on binary classification with 60 features. class 1 is of 1554 records and class 2 is of 3558 records. Now I would like to find the risk factors that ...
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1answer
33 views

Threshold to consider new feature as a new finding to a model?

I am working on binary classification problem with 5K records and 60 features. Through feature selection, I narrowed it down to 14 features. In existing literature, I see that there are well-known 5 ...
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1answer
37 views

ML Project - Achieve 2 Objectives

I have a dataset with 5K records focused on binary classification. I am posting it here to seek your suggestions on project methodology Currently what is my objective is 1) Run statsmodel logistic ...
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2answers
45 views

Which metric to choose for tracking model performance?

I am working on a binary classification problem with class proportion of 33:67. Currently what I am doing is running multiple models like LR,...
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1answer
45 views

How to select best feature set and not ranking for tree based models?

I am currently using feature selection approaches like filter, wrapper, embedded etc. All these methods give different set of ...
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2answers
334 views

Auto ML vs Manual ML for a project

I recently was introduced to a AUTO ML library based on genetic programming called tpot. Thanks to @Noah Weber. I have few ...
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1answer
463 views

feature selection using genetic algorithm in Python?

I have a dataset of 4712 records and 60+ features working on a binary classification problem. I already tried out all the feature selection approaches like ...
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1answer
56 views

1: 10 rule in logistic regression - EPV

I have a dataset with 4712 records. Label Yes - 1558 records and Label No - 3554 records. I read online that ...
2
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1answer
62 views

What is the difference between horizontal and vertical ensemble?

I am looking at different ways to do model ensembling and I came across the terms horizontal and vertical blending/ensembling but it is not well defined. My questions will be: What is the ...
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2answers
67 views

How to perform bootstrap validation?

I am working on a binary classification problem. I ran cross-validation and grid-search on train data. Later I validated the model on my test data as shown below ...
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3answers
52 views

Training on derived features that won't be present in a test set

So I have an odd real-world problem in which the data that's going to be fed to a categorical predictive model has (a few) certain features, and when building a model I can bolt on additional datasets ...
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1answer
21 views

How is DS used in the case of Payment Gateways?

I know it's a general question but what type of analytics can be done in this case? How can we apply machine learning models here?
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2answers
83 views

How to adjust cofounders in Logistic regression?

I have a binary classification problem where I apply logistic regression. I have a set of features that are found significant. But I understand that Logistic regression doesn't consider feature ...
2
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1answer
27 views

How to justify a predictor in influencing the outcome?

I am working on a prediction (binary classification) problem Currently I get an AUC score of 85-86 and F1-score of ...
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1answer
57 views

How to interpret shapley force plot for feature importance?

I am trying to practice and learn shapley value approach to explain my predictions on a binary classification problem. However am having difficulty in understanding the below plot. 1) Does it ...

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