Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

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0answers
13 views

Space partitioning to estimate product weight

Looking for some vocabulary to help me refine my research so I can tackle this problem. Here's an overview of the problem statement I'm working on. At my company we manufacture various products, ...
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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 ...
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1answer
25 views

How to adjust/smooth a certain number using constants or rules

Hi, I am handling a dataset with a customer purchase history. The field ord_cnt represents the purchase without coupon usage, and cpn_ord_cnt represents the purchase with coupon usage. There are two ...
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1answer
36 views

best NN architecture for point prediction

I'm training to predict a single value y (continuos in [0,1]) based on a number of variables ...
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1answer
31 views

Prediction for not completely well classified data

I have a DataFrame of users, some of them are "bots" and they are identified with a bit equal to 1 in the "is_bot" column, if the bit is 0, the user is considered as "human". The problem is that some ...
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2answers
90 views

Custom loss function

Is it possible to apply a custom loss function in a regression model (or any other algorithm for predicting continuous variable) ? I'm working on a stock market prediction model and I need to maximize ...
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14 views

can i compare output from predict_proba with my y_test value?

all, i am a bit confused at comparing my results from predict_proba (which returns an array) to it's dataframe e.g ...
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16 views

Public benchmark datasets posted with expected/record scores for sanity check?

When I use a new modelling tool or approach, I like to do a quick sanity check on a public dataset to make sure I'm getting good (but not "so good it looks fishy") scores. There are several clean, ...
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16 views

Building the right prediction process with machine learning

I am working on a two-class classification model to predict if some lead becomes a sale. At this moment I have all leads try to predict these ones, which are sales. I become good metrics right now ...
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1answer
55 views

How to make prediction using tensorflow models?

As a newbie to tensorflow, I am using this tutorial from google for binary classification using a simple dense neural network. The slightly annoying thing about this (and a few other) tutorials is ...
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4answers
147 views

How to improve results in classification problems (SVM, Logistic Regression and MultiNaive Bayes)?

I am new on Machine Learning and building models but a lot of tutorials has given me the chance to learn more about this topic. I am trying to build a predictive model for detecting fake news. The ...
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19 views

Defining the Target Value

im new to this community and it always helped me with my concerns, i looked for an answer but didnt find a clear one yet im working on study for insurance default, the data i received is already ...
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0answers
17 views

When should I reverse normalizations to evaluate loss?

If I am training a neural network and have normalized the data before-hand, should I reverse the normalization to calculate the loss? This tutorial provides an example of this method. What if I'm ...
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3answers
496 views

Does shuffling data for time series forecasting help?

So I am trying time series forecasting using LSTM's. The aim is to predict $Y$ given $X$ using regression. I had already converted the input data into a sliding window format such that if my input ...
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1answer
242 views

Logistic regression based prediction model using flask(python) to predict if Student will pass or fail. Error [duplicate]

I am trying to create a web application on Python using Flask that predicts if a student is likely to pass or fail using a Kaggle dataset. I changed the dataset a little and want to predict if the ...
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1answer
17 views

Low leves of probability observed after modelling.Is it right to scale the probability

I have done modelling on imbalanced class , without any sampling methods. Event rate is around 0.1 ,After modelling I am getting probalities more at the lower side close to zero.I have tried differnt ...
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1answer
48 views

What's the best way to predict weekly selling data?

I am trying to create a model to predict the units that will be sold for different grocery items say in the next week. I am structuring the problem in a three-step procedure. Group together the ...
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1answer
42 views

Two-class model with predicted scores needed - classification or regression approach

In my problem, step one is to build a model to classify cases as one of True or False (1 or 0 could also be used obviously). Once the optimum model is found, step two is to retrieve probabilities for ...
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1answer
26 views

Predicting a timeseries that includes categorical and numeric data

Given the following properties in a dataset: Type Of Work [T1,T2,T3,...Ti] Measurment Unit [U1,U2,U3,...Ui] Number ...
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20 views

Predicting next failure of car system given previous failures

I have a Dataset of cars including various features just as energy used, power, the model year, rolling law (maximum number of kilometers the car should drive per year) etc. I have also some ...
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24 views

Which type of model should I use to predict when a time-series value will revert towards the mean?

I have a time series that consists of many rows, each with a timestamp, and a value between -1 and 1 representing the normalized price distance between 2 financial assets. Each entry is roughly evenly ...
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1answer
88 views

Hill Climbing Algorithm - Optimum Step Size

I am implementing a standard hill climbing algorithm to optimise hyper-parameters for a predictive model. The hill climbing algorithm is being applied as part of a two-stage approach: Apply grid ...
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1answer
15 views

how to perform minmax normalization on large dataset?

I have problems loading it at once. I guess this problem applies to compute all the variables that need to take the whole dataset.
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16 views

Weighting Value Of Timer Series Event Based On Subsequent Events

I am new to Data Science forum. I post a lot on StackOverflow, but this issue is more conceptual. I am doing analysis on time series data and weighting the value of an event based on the outcome. ...
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1answer
28 views

How to measure Covid impact by analysing credit card transaction of customer

I Want to know how can I identify that is the customer is in financial distress due to the COVID situation using its credit card transactions. I have a daily transaction of customers till current ...
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0answers
28 views

How do I approach this problem?

Let's say I have a dataset with multiple types of multiple ingredients ($salt_1$,$ salt_2$, etc). Each $n\text{-th}$ variation of each ingredient vs flavor may be represented by an $n \times k$ matrix ...
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2answers
37 views

How to choose best model for Regression?

I'm building a model to predict the flight delay. My dataset contains the following columns: FL_DATE (contains months(1-12)), OP_CARRIER (One hot encoded data of Carrier names), ORIGIN(One hot ...
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17 views

Fit model function out defined data range

I have asked this on SO but it has not been well accepted because it seems to be more about data science than programming. Let's say I have a set of data ...
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1answer
52 views

Multiclass classification dataset with many features producing bad accuracy of predictions

I have been trying to fix this for 2 months now with no luck. I am doing some medical research for my study. I have a dataset that has patients diagnosis based on medical reports (Features.csv) and ...
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1answer
476 views

How to consider categorical variables in distance based algorithms like KNN or SVM?

For example lets say I have a dataset with independent features age, gender, name, and income. While my dependent variable is load approval status. If I want to use KNN or SVM, do I need to convert ...
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1answer
24 views

Identifying members who are likely to move to a lower cost alternative product

Overview: I am looking for some technical direction from the ML/data science community about how I could tackle my business problem. Context: In a nutshell, I have a group of customers who ...
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0answers
23 views

Any good source to find nCOVID-19 latest trends and forecasts for analysis? [duplicate]

I am searching for trends and dataset in both .csv and api format to do predictive analysis on Coronavirus for various countries. What are good sources to browse such datasets?
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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 ...
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2answers
39 views

Update the saved model after training

Will saving a trained model this way give me a model trained on every chunk of data or just the last chunk? ...
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1answer
271 views

Why is oversampling outperforming class weight?

I have a dataset that is highly imbalanced. One class has 412 (class 0) samples while the other has 67215 (class 1) samples. For its classification, I am using MLP. When I use class weight of 165 for ...
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2answers
244 views

Compare Classification Performance in Datasets drawn from Different Populations

I've read some classics about comparison of ML Algorithms i.e. ...
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16 views

How to model a decimal response between 0 to 1 with a GLM in R

I am trying to model a response variable which is a proportion (so a response between 0 and 1, see picture for distribution). Ideally I would like to model it without using the actual counts, so as a ...
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0answers
15 views

Measuring the bias of a machine learning model

How can we measure the bias of a machine learning model? Can we determine it by just calculating its performance estimates difference on the train data and test data? For example, if a model SVM ...
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1answer
72 views

gradient descent diverges extremely

I have manually created a random data set around some mean value and I have tried to use gradient descent linear regression to predict this simple mean value. I have done exactly like in the manual ...
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1answer
30 views

Dimensionality reduction and prediction when all columns have approximately same variance

I have a dataset of 25 columns where the goal is to predict the value of the 25th column based on the previous 24 columns. The dataset is quite big that's why I initially thought to proceed with PCA ...
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1answer
23 views

Ngram based Langauge Models learned using an Encoder-Decoder Model

I have been going through a Ngram based Langauge Model learned using an Encoder-Decoder Model for Email smart compose. The program output only 1 prediction for given input. I want to know how to ...
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0answers
36 views

“Smearing” probabilities or how to handle imprecise locations for canonically classification-type problems

I am trying to predict failures at different nodes on a line. Each node has different weather features and hardware/configuration features. For a little under half of the historical failures I have, I ...
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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 ...
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1answer
204 views

Brownian motion in models for virus spread?

Was reading a Washington Post article "Why outbreaks like coronavirus spread exponentially, and how to flatten the curve” and it looked like they were using Brownian Motion. (Can't directly link the ...
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1answer
68 views

Model to predict coronavirus (covid19) spread [closed]

im new in data sience and machine learning but i have some mathematical and statistics backgroud. I really just want some information about models (like papers or raw models). So if you have any ...
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1answer
110 views

TF Keras Text Processing - Classification Model

I'm trying to put together a script that classifies comments into either adequate or inadequate. I put a question up here earlier with all my code, but I think I've isolated the problem down into the ...
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1answer
28 views

Best way to evaluate performance for my case

I have dataset that looks like this ...
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0answers
49 views

Hedge fund rank on their returns or rating predictions modeling problem

Problem: Hi, I m a new machine learning practitioner. I have a dataset about hedge funds. It contains monthly hedge fund returns and some financial metrics. I calculated metrics for every month from ...
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22 views

Forecasting sales during time of epidemic

As we are going through a tough time because of the Coronavirus epidemic, is it possible to somehow include this affect of this in predicting sales as a time-series for next few weeks? I am new to ...

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