Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

310 questions with no upvoted or accepted answers
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1answer
88 views

Predicting change of shapes/coordinates

I'm trying to find a way to predict/calculate how a shape (e.g. outline of a glacier) will change in the future—based on its history (previous shape) and additional factors (e.g. Δtemperature). In my ...
4
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2answers
221 views

Support Vector Regression trained with data sets

I am now searching for a long time on the internet and on papers for an answers of simple questions. Am I able to train a Support Vector Regression algorithm with different data sets? If yes, how is ...
4
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2answers
2k views

fix first two levels of decision tree?

I am trying to build a regression tree with 70 attributes where the business team wants to fix the first two levels namely country and product type.To achieve this,I have two proposals: 1.Build a ...
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 ...
3
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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 ...
3
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1answer
60 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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0answers
33 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: ...
3
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1answer
72 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 ...
3
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1answer
102 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
50 views

Is linear regression on the trees of XGBoost (rather than taking their mean) useful/popular?

Given training data $(\underline{x}_1, y_1),...,(\underline{x_N}, y_N)$, one can choose a variety of ensemble method for trees. These algorithms output a set of trees $T_1, ..., T_n$, and then the ...
3
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1answer
53 views

Predicting t+1 from a set of sequences

Say I have have an experiment where I release a single rat into a maze and wait for it to reach the end. Say I also track this rat's position in the maze at various times. Let's do this $n$ times. Now,...
3
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1answer
593 views

Connection between cross entropy and likelihood for multi-class soft label classification

The connection between cross entropy and log likelihood is widely expressed for the case when sample multi-class labels are one hot binary vectors (basically the same). Cross entropy is defined when ...
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0answers
151 views

Multiple models vs. Single model for prediction

I am using the Darknet Convolutional Neural Networks to detect people (as in, humans) and furniture in a single image. If I train the model twice, one for people, one for furniture. I seem to get ...
3
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1answer
2k views

Why is Spark's LinearRegressionWithSGD very slow locally?

I have been trying to run linear regression with SGD that is found in Spark mllib for some time and I am experiencing huge performance problems. All examples that I was looking have number of ...
3
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0answers
1k views

How to predict Estimated Time for Arrival given only trajectory data and time?

I have data of latitude, longitude and timestamp. I am trying to build a graph based on pincodes (in India) (equivalent to zipcode). Based on this graph and trajectory data that I have, I want to ...
2
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1answer
17 views

How to present longitudinal data to LSTM for multiclass prediction

I need to implement a deep learning algorithm to predict an ordinal value, called 'Entity', using longitudinal health records data. I read a few articles and guides but I couldn't find a clear ...
2
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0answers
19 views

History that lead to the word “predict” being used for the application of a model on data

Background The framework scikit-learn uses "predict" for the application of model on (new) input data and I have seen many people use that term. In the scientific papers that I have read (...
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0answers
51 views

flexibility vs complexity vs number of predictors in machine learning

I'm new to machine learning so am quite confused with the above concepts. It seems to me both flexibility and complexity measures how well the model fit the data (in terms of the curvy-ness), so what'...
2
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1answer
105 views

1st order Taylor Series derivative calculation for autoregressive model

I wrote a blog post where I calculated the Taylor Series of an autoregressive function. It is not strictly the Taylor Series, but some variant (I guess). I'm mostly concerned about whether the ...
2
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1answer
41 views

what are the next step after ML prediction and how to proceed?

I have trained an ML model with a good accuracy but what next? I am facing difficulty in answering this question, how will you present your model. Which framework do you use How do you make sure ...
2
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2answers
43 views

How to decide who to market? Clustering or Decision Tree?

I am working with a dataset that has enough observations and ~ 10 variables, half of the variables are numeric another half of the variables are categorical with 2-3 levels (demographics) one ID ...
2
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1answer
62 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 ...
2
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0answers
124 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 ...
2
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1answer
52 views

Gaussian Naive Bayes (GaussianNB) classifier not working with large number of features

I'm trying to make a partial fitting with GuassianNB here's small snippet of my code ...
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0answers
104 views

Omnibus and R square improvements for OLS model

Checking on this community if any one can help with this problem posted on Cross Validated. Detailed question is as below: ...
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0answers
55 views

How to predict constant failing of equipment

I am trying to predict the failing of an equipment that heat up the liquid in a pipeline using a heat exchanger. The heat exchanger gets build up inside the pipe and thus needs to be flushed every ...
2
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0answers
32 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 ...
2
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0answers
32 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 ...
2
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0answers
66 views

Why do you need to use group lasso with categorical variables?

From what I've read you should you use group lasso to either discard the dummy encoded variables (of the category) or use all of them. If you use normal lasso then some of the variables in the group ...
2
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0answers
121 views

Out of stock / Spike in demand prediction

The goal is to predict out-of-stock situations, either quantitatively (the gap) or qualitatively (out-of-stock likely to happen in next few weeks). Background: We have existing demand planning ...
2
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0answers
192 views

Target Variable Encoding for Time Series Change point detection

I am working on a time series data for which I intend to impliment machine learning model for detecting change point in time series data. This data is recorded fom machinary and we have to predict ...
2
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1answer
236 views

Model prediction on meshgrid in python

Suppose I have data with two independent variable $X_1$, $X_2$ and one dependent variable say $y$, as follows: $X_1$: $x_{1,1}$, $x_{1,2}$ , $x_{1,3}$ $X_2$: $x_{2,1}$, $x_{2,2}$, $x_{2,3}$ $y$: $...
2
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1answer
45 views

Estimating location in a model

I have a big dataset with 10 columns and about a 100,000 rows. Each 5 rows represent a person being tracked and the data related to this tracking such as time, velocity, etc. the last two columns are ...
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0answers
33 views

Multiclass classification problem with more prediction classes than real classes

Can I have a multiclass classification problem with more prediction classes than real classes? For example: I want to predict the channel the user is going to watch. The real classes are "user didn't ...
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0answers
37 views

Using datasets to predict the results for other devices

I have a datasets that contain results from a series of physical tests. It has about a dozen features and the outcome of each test is distinguished by 3 different classes. The dataset includes ...
2
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0answers
901 views

How to implement Moving window with LSTM for Time Series Prediction?

I am trying to implement a moving window in my dataset. The window size=14 (for instance).After implemntinf sliding window how to prepare inputs and outputs for netwok? ...
2
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0answers
58 views

ML/Statistical Model to Analyse the Distribution

Consider a Sample Data-set provided below; ...
2
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1answer
66 views

Ranking ATM based on Utilization and Economic Data (Scoring/Rank Model)

I have a sample data of around 10 ATM's Locations along with their Utilization Count (Deposits, Withdrawals and Others) for the past 3 months. I am planning to collect additional data such as nearby ...
2
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0answers
58 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. ...
2
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0answers
203 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 ...
2
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0answers
124 views

decision tree vs neural network for boolean function

Which structure is more powerful in terms of expressiveness (i.e. it can represent a given Boolean function, accurately) — a single-layer perceptron or a 2-layer decision tree? (There are 10 features)
2
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1answer
89 views

Need help on Time Series ARIMA Model

I'm working on forecasting daily volumes and have used time series model to check for data stationarity. However, I'm strugging at forecasting data with 90% accuracy. Right now variation is extremely ...
2
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0answers
52 views

Split large dataset for predictive modeling using rsparkling -sparklyr

I am trying to build machine learning models (GBM, RF, Staking) on top of a dataset that is about 3G in size on my local computer. However, I only have 4G memory (only 2G are available). My question ...
2
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1answer
105 views

Store's unseen items sales forecasting

I am working on sales forecasting problem.I am able to provide data about which items got sold and not sold to the algorithm.How to provide algorithm information about items that are not present in ...
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0answers
49 views

How does SVD actually provide the recommendations? I seem to get conflicting answers

I am reading a text book that basically says the following: Given a matrix A where A is USERS x ITEMS we can use SVD to decompose the matrix into: $$A = U \times \Sigma \times V^T$$ Then we can take ...
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0answers
215 views

How to use HMMs for continuous value prediction

I have some time-series data, which I need to use to predict a continuous value for a given time-stamp. I was initially doing it using a Multivariate Regression Model but I later figured that a time-...
2
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0answers
1k views

predict() returns NA values

I have the problem. predict() method returns NA. My plan is: Read data from file and separate data to 2 sets: test and train Remove column with NA fraction over 95% Replace NA values with mean value ...
2
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1answer
135 views

Model building with neural networks

Assume the existence of a collection of physical parameters and a collection of output variables which may depend on the physical parameters. An example in the training dataset consists of a vector ...
2
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0answers
112 views

how to use machine learning or network analysis to prevent contagious disease

I would like to share a question about my research. I have data about networking of a contagious disease. I have 60 pigs, and I have the contact time with others pigs of each individual in 28 study ...
2
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0answers
460 views

randomForest::varImp VS conditional variable importance

Data: My training set consists of ~450k obs and 26 variables, out of which 1 is an ordinal factor (order_month, 12 levels) and the rest is numerical. Moreover, some of my predictors are highly ...

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