Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

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40 views

How to distinguish informative and non-informative feature - Feature importance?

I have a dataset with 5K records focused on binary classification problem. I have more than 60 features in my dataset. When I used Xgboost, I got the below ...
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1answer
54 views

How to Maximize recall for Minority class?

I have a dataset with 4.7k records and 60 features. 1558 records of indication label 1 and 3554 records indicating label 0. Am ...
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1answer
24 views

Mismatch between optimum features and grid scores using RFECV?

I have a dataset with 5K columns focused on binary classification. I have more than 60 columns. I am trying to find the best features through RFECV approach. Though it produces 30 optimum features, ...
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1answer
20 views

How can calculate Efficiency for predictive models based on accuracy or error over time?

I was wondering if I could express the efficiency of prognostic models according to their accuracy(error, e.g. MAPE or MSE) over time [sec]. So let's imagine I have the following results for different ...
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1answer
56 views

How to define the number of features to select in RFECV?

I am trying to work on feature selection stage for my dataset. I am a newbie to ML. I have around 60 columns and am trying to select top 15 features. I came to know about RFECV for which I wrote a ...
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2answers
163 views

How to select features for a ML model

I have a dataset with 5K records for binary classification problem. My features are min_blood_pressure, max_blood_pressure, <...
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1answer
31 views

Evaluating likelihood of egg breaking when falling in random container on concrete [closed]

I am working on a project where I would like to predict whether an egg will break if it is put in a container that is then dropped on concrete. I am looking at the different factors that play a role ...
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0answers
14 views

Sales Prediction for multiple customers

In e-commerce, there will be lots of customers but each customer sales will be limited in number of records? In some cases, the records will be less 5 also. In cases like this, how to predict the ...
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0answers
18 views

Using Keras/TS for Multivariate Time Series Prediction w/ Univariate output?

I've been reading through a few tutorials for using Keras/TensorFlow for multivariate time-series prediction (primarily using LSTM models). One example uses air pollution as an example. In this ...
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0answers
11 views

How to Predict Employee count of businesses using Keras classifiers

I am trying to predict the amount of employees a business has based on a set of input variables. I am using things like the business's age, transaction details, geographic location, business structure ...
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0answers
25 views

Predict numerical value when each variable is a target and a predictor

Imagine I have created a tabular dataset when each row is a company and each variable is the company's rating between 0 through 100 given by a rating agency. Each of the ratings agencies can decide ...
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1answer
44 views

Sequence to carry out data analysis?

I have a dataset with 4700 records and it's a classification problem. Proportion of classes is 33 and 67% few questions 1) does this proportion qualify dataset as imbalanced ? 2) should I do ...
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1answer
14 views

Error while using predict [closed]

After splitting into test and train the glm function is used on train set. For example m1 = glm(target ~ ., data = train, family="binomial") Then ...
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2answers
36 views

Logistic regression threshold value

How can i set the threshold value for the target variable. For example if a target variable is chance_of_admit and it has values from 0 to 1, how can I pick a value and so that I can convert it to 0's ...
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0answers
26 views

Model Guardrails

Suppose I am building a machine learning model for an application where I do not need to make a prediction on all new samples, and given a new sample, it is better to make no prediction at all when ...
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0answers
7 views

how to package PMML files for versioning?

I am looking to package PMML file generated to export tree model. Are there any existing standards which describe how to package and version PMML files ?
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3answers
58 views

How can we convert time series data to supervised learning problem?

I am preparing a data for machine learning model. I want to deal with time series data as normal supervised learning prediction. Let's say I have a data for car speed and I have several cars models ...
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0answers
15 views

Is it useful to consider a categorical features into a `polynomial` or `linear model`?

In Titanic dataset, i have a dataset containing Categorical features (such as Cabin, Embark and Sex). I need to build a linear or polynomial model with multiple variables to predict ...
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2answers
28 views

Does Sampling size matters in Multi classification Model

I am working on a multi class classification model where few of the class are with less data compare to other classes. I used random sampling technique to create a sample from the population keeping ...
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2answers
100 views

model with features of different sizes

I want to train a model (either classification or regression, doesn't matter) with features/inputs of different sizes, but I am not sure how to do it. For example, for each data-point, feature 1 and ...
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0answers
16 views

How to deal with a particular month being under forecasted by the model?

I have 6 cycles of historical time series data of retail sales and using a prophet model to forecast one cycle. I am using 4 variables as regressors. There is one month in particular - 'April', which ...
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0answers
56 views

Prediction error without having a true value

Quick summary about the problem: we are trying to deploy our regression model, where the clients require "individual prediction error". Since we're predicting something unknown in advance, we can't ...
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0answers
24 views

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
32 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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1answer
25 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
28 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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0answers
14 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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0answers
23 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
38 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
35 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
34 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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0answers
18 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
35 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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0answers
14 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
149 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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0answers
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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0answers
15 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
44 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
34 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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0answers
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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0answers
10 views

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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0answers
23 views

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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0answers
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
13 views

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
70 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
27 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 ...
1
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1answer
45 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
155 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
20 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 ...