Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

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3answers
63 views

Whether Interaction terms should be included in Linear Regression analysis?

I am working on a linear model with 6 independent variables and when thinking about including an interaction I got lost. An interaction exists if the level of one independent variable is affected by ...
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2answers
30 views

Machine learning and time-based data

I want to predict conversion rates for an eCommerce store. I have data from Google Analytics with features like averageSessionDuration, bounceRate, numberOfVisitorsBySource etc. and the corresponding ...
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0answers
23 views

Unstable Training when combining Graph Neural Networks for Graph Classification Tasks

I have been combining Graph Convolutional Layers and Graph Pooling layers to define a neural network architecture for Graph Classification tasks. Specifically, using the Graph Convolutional Layer ...
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1answer
63 views

How many images can be trained in Google Colab? [closed]

I am using the ResNet50 pretrained model to train my images using TensorFlow. I have 70k images and upgraded to Google Colab Pro, but still I am facing a memory error. So how many images I can train ...
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44 views

Interpreting the results of the probabilistic neural networks (Monte Carlo dropout approach)

I have a Keras NN model where I apply the Monte Carlo dropout approach as a predictive method to evaluate the uncertainty of the model outputs. From my research in the probabilistic neural networks, I ...
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15 views

Calculating Uncertainty for categorical predictions

I am wondering what is the best way to calculate the uncertainty for my categorical predictions. I have created a model that predicts what rating a movie is getting based on certain keywords and the ...
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1answer
49 views

How data are prepared during training, testing and in production?

Most of real world datasets have features with missing values. Replacing missing values with an appropriate value such as its mean, is considered as a good step in feature engineering. Some times we ...
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0answers
10 views

Classification model performance - metrics for getting number in each class correct?

I'm fairly new to predictive modelling, so apologies if this is a stupid question. I am working on a classification problem (predicting if customers commit fraud or not), and have been comparing a few ...
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3answers
46 views

Metric to punish positive errors

I'm involved in a ship transit time prediction project. Is about prediction the time that a ship's cargo takes to go from port A to B in order to contract the fastest carrier company and tell the ...
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10 views

Predict the target audience for a new brand using data from other brands and customers buying behavior

Assume a company has a large database about wine, including brand, the taste of the wine, year, place of production, etc, and data of customers' purchase behavior. Now if there is a new brand coming ...
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1answer
14 views

After training and saving a model can we give more information as input?

Suppose my data is a time series with multiple features such as wind, temperature, holidays, etc.. and I'm predicting a target variable Y. After I go through the whole process of splitting data into ...
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20 views

How to ouput buckets of probabilities?

I am dealing with an unbalanced binary classification problem. The problem is so unbalanced (2:98) and hard to predict that I am interested in probability of the positive outcome instead of trying to ...
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0answers
38 views

How to predict auction winning price without knowing the winning price when you lose the auction?

Suppose I participate in online auctions. I submit bids based on the features of the item being sold, but I only got feedback when I win. If I lose, I would know nothing about who won, and how much ...
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1answer
25 views

Using Information from the rest of a Sequence to Predict the Label for any one Item

I have a dictionary of variable-length sequences: [(file_name[-10:], len(tag_is_header_list)) for file_name, tag_is_header_list in HEADER_PATTERN_DICT.items()] <...
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2answers
61 views

Predicting the likelihood that a prediction from a linear regression model is accurate

So to set up the problem: I have a data set that had labeled data like colour, brand and quality as independent variables and the dependent is RRP (price). I have made a linear regression model using ...
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1answer
79 views

Model retraining

I have trained my model with RandomForestRegressor, but now my training data is updated continuously. So I have to train my model with all the train data set i.e past and new data, or can I directly ...
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45 views

How to predict variables based on multiple samples?

The problem I tried to do some ML models but everytime I had some weird plots and I couldn't understand these scores. I'm relatively new to ML and maybe someone can help me with this data with some ...
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3answers
22 views

Is it possible to create a predictive model for a dataset that consists of only positive occurrences of the dependent variable?

Lets say I want to predict earthquakes. My dataset would only contain data about earthquake occurrences and no data about non-earthquake occurrences as that would basically be any other period of time ...
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2answers
26 views

How effective would a data-driven vaccination program be over a simple rules based approach

The rollout of vaccination programs tends to be based on a given set of rules (advice) devised by government UK example. Such a rule-set are generally limited in complexity in order to be consistently ...
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1answer
39 views

How to handle One Hot Encoded columns with changing categories in supervised ML Problem?

Scenario: I have the following game data about participants, game and the winner in the following format: ...
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1answer
12 views

multi items forecasting: issue with storing results

disclaimer: I am not 100% sure that this is the appropriate place to ask this question. Here is a little bit of context about the problem. I have a dataset containing about 1000 products timeseries (...
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1answer
28 views

Relationships between groups of features against independent variables

I have several groups of features that I'd like to test against independent variables. The idea is to find which groups tend to be associated with a specific value of an independent variable. Let's ...
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1answer
33 views

How to Include Features that Apply to Specific Classes

I'm predicting hours that will be worked for building tasks. Due to the overall low sample size, I've stacked multiple related tasks together into a single model. (There may be 100 total samples in a ...
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19 views

Prediction using OSM and Airbnb Listing dataset

I am building a model to predict the price of an Airbnb listing. Using OSM("https://wiki.openstreetmap.org/wiki/Downloading_data") and Airbnb listing("http://insideairbnb.com/get-the-...
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10 views

Predicting an annual event – modeling on an annual or monthly basis?

Suppose I'm interested in predicting which of my current customers are likely to renew their insurance at some point in the year. The renewal can happen at any time in the year. I want to proactively ...
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21 views

how to interpret this 'lift chart'? prediction and true labels

i am trying to compare the prediction from my classifcation model and it's true label either 0 or 1. ...
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1answer
84 views

Negative R2_score Bad predictions for my Sales prediction problem using LightGBM

My project involves trying to predict the sales quantity for a specific item across a whole year. I've used the LightGBM package for making the predictions. The params I've set for it are as follows: <...
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1answer
49 views

Predictive model to maximize sum of dependent variable?

I am trying to classify cars for a towing company. Junky cars earn more when sent to the junkyard, and the more valuable cars should earn more at the auction, despite the auction fee. Creating a ...
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0answers
18 views

How to aggregate Weather Data from county to state level? [closed]

I am doing a prediction of forest fire risk using the weather data and the fire incident data. I have data related to different county and the weather data on the day of the incident. As the incident ...
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2answers
71 views

Predictive modeling when output affects future input

Assume I have a model which predicts the outcome of number of icecream sold in a store. The model is trained on data for the last 5 years while keep the last year as a validation set and has produced ...
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1answer
46 views

What Machine Learning Technique can I use to judge boxing fights? [closed]

I want to build a machine learning model that judges the fights based on the results of each round. Any suggestions on what techniques can I use?
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26 views

optimizing customization: beyond a combinatorial approach?

Say I have a generic non-linear model (ANN, Random Forest, Gradient Boosting, etc) that wants, based on a set of features (price of a product, service duration, age, etc), to give me a prediction of ...
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2answers
63 views

How to build a model on a dataset having 40% missing values in most of the variables?

I have a huge dataset of 10 million observations but most of the variables are missing for 40% records. There are couple of variables available for the whole dataset such as sic code(Industry category)...
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1answer
21 views

Can a Box plot be used for finding the useful features from the dataset? [closed]

I am reading a book by professor Trevor Hastie and professor Robert Tibshirani called "Introduction to Statistical Learning". In the applied section of the chapter 4, there is a question 11(...
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1answer
21 views

Predict real world data after modelling with scaled features [duplicate]

I trained and test a model with scaled features. Now, I want to predict a single real world sample. If I have one sample alone, I can't scale it to fit into the model like I did with the test data. I ...
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1answer
19 views

Should I perform customer segmentation before performing churn prediction?

Imagine a company with multiple lines of revenues coming from diferent products, but all customer can access these different products through the same account and the same online platform. My goal is ...
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2answers
2k views

How to split train/test datasets having equal classes proportion

I would like to know how I can split in an equal number the following Target 0 1586 1 318 in order to have the same proportion of 0 and 1 classes in a ...
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0answers
34 views

KL Divergence between Predictions and Ground truth

I've got four (non-linear, tree-based) models in production and using the average of them as the served prediction. We get ground truth data immediately. During training the optimized candidate models ...
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1answer
31 views

Predictive output with your own model built

I would need to better understand how can be created a machine learning algorithm from scratch using an own model developed based on boolean values, for example # of words in a text, # of punctuation, ...
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0answers
27 views

How to model a conditional demand forecast model as ex-ante forecast for a moving population?

Goal: I am trying to forecast demand from a specific population given a specific promotion on a certain period of time frame. The data is of the format: date | promotion % | sales in 1000s(y) 01-Jan |...
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1answer
72 views

What is the best machine learning model to predict a continuous variable where the predictors include categorical, numerical variables and a text?

The variables include categorical variables like (contains video, author) and numerical variables like (average word length) and a text (combination of words). I am confused about this because from ...
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0answers
18 views

Why does my model fail to predict on the whole dataset?

So I have about 3000 images with 6 classes and this is what I did: 1 - split into training set and test set prior to anything with 20% test size 2 - performed data augmentation on the under ...
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1answer
47 views

Sir Rod Stewart's and Celine Dion's voice after 15 years i.e. Year 2035 [closed]

https://www.google.com/search?sxsrf=ALeKk03hQn_rH1aaf7yO0q7CgN7CxPw2vw%3A1601345036018&ei=DJZyX9BW_o_j4Q-Fn77QCg&q=rod+stewart+age&oq=Rod&gs_lcp=...
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3answers
412 views

How do I use lagged independent variable in statsmodel OLS regression?

If there is good reason to believe that an independent variable (x) has a lagged effect on dependent ...
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0answers
37 views

How do I model time series data that contains a unique ID and a constant time step?

My data currently looks like this (after processing, 15 mins timesteps): ...
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0answers
47 views

Visualization of transformed features in BERT

So I'm trying the Intent Recognition with BERT using Keras and TensorFlow 2 available at kdnuggets.com and this is the code for the results evaluation. ...
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0answers
86 views

What's the order in applying SMOTE transformation in a pipeline?

Here's the thing, I have an imbalanced data and I was thinking about using SMOTE transformation. However, when doing that using a sklearn pipeline, I get an error because of missing values. This is my ...
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1answer
138 views

Hyperparameter Tuning in Random Forest Model

I'm new to the machine learning field, and I'm learning ML models by practice, and I'm facing an issue while using the machine learning model. While I'm implementing the ...
3
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1answer
60 views

Neural Network regression negative performance

I have a problem with the performance of a multi layer perceptron regressor (neural network) and I cannot figure out why. Task: I am trying to improve a time series prediction. I have predictions of a ...
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0answers
41 views

Time series stationarize vs normalization

I have multiple time series coming from sensor measurements of an industrial machine. The industrial machine runs different 'Recipes'. Every recipe has different set of parameters which are set before ...

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