Questions tagged [predictive-modeling]

Statistical techniques used for predicting outcomes.

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53
votes
8answers
14k views

Why Is Overfitting Bad in Machine Learning?

Logic often states that by overfitting a model, its capacity to generalize is limited, though this might only mean that overfitting stops a model from improving after a certain complexity. Does ...
48
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5answers
44k views

Should a model be re-trained if new observations are available?

So, I have not been able to find any literature on this subject but it seems like something worth giving a thought: What are the best practices in model training and optimization if new observations ...
26
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1answer
9k views

Time Series prediction using LSTMs: Importance of making time series stationary

In this link on Stationarity and differencing, it has been mentioned that models like ARIMA require a stationarized time series for forecasting as it's statistical properties like mean, variance, ...
23
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2answers
19k views

Predicting a word using Word2vec model

Given a sentence: "When I open the ?? door it starts heating automatically" I would like to get the list of possible words in ?? with a probability. The basic concept used in word2vec model ...
22
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3answers
67k views

How to predict probabilities in xgboost?

The below predict function is giving -ve values as well so it cannot be probabilities. ...
18
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5answers
6k views

Merging sparse and dense data in machine learning to improve the performance

I have sparse features which are predictive, also I have some dense features which are also predictive. I need to combine these features together to improve the overall performance of the classifier. ...
15
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3answers
37k views

What does “baseline” mean in the context of machine learning?

What does "baseline" mean in the context of machine learning and data science? Someone wrote me: Hint: An appropriate baseline will give an RMSE of approximately 200. I don't get this. Does he ...
15
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3answers
646 views

Why are ensembles so unreasonably effective

It seems to have become axiomatic that an ensemble of learners leads to the best possible model results - and it is becoming far rarer, for example, for single models to win competitions such as ...
15
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1answer
48k views

Train Accuracy vs Test Accuracy vs Confusion matrix

After I developed my predictive model using Random Forest I get the following metrics: ...
14
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3answers
13k views

Is feature selection necessary?

I would like to run some machine learning model like random forest, gradient boosting, or SVM on my dataset. There are more than 200 predictor variables in my dataset and my target classes are a ...
14
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2answers
8k views

How to train model to predict events 30 minutes prior, from multi-dimensionnal timeseries

Experts in my field are capable of predicting the likelyhood an event (binary spike in yellow) 30 minutes before it occurs. Frequency here is 1 sec, this view represents a few hours worth of data, i ...
13
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5answers
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? ...
12
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1answer
5k views

Hashing Trick - what actually happens

When ML algorithms, e.g. Vowpal Wabbit or some of the factorization machines winning click through rate competitions (Kaggle), mention that features are 'hashed', what does that actually mean for the ...
11
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4answers
26k views

How to avoid overfitting in random forest?

I want to avoid overfitting in random forest. In this regard, I intend to use mtry, nodesize, and maxnodes etc. Could you please help me choose values for these parameters? I am using R. Also, if ...
11
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2answers
8k views

How to perform Logistic Regression with a large number of features?

I have a dataset with 330 samples and 27 features for each sample, with a binary class problem for Logistic Regression. According to the "rule if ten" I need at least 10 events for each feature to be ...
11
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3answers
1k views

What regression to use to calculate the result of election in a multiparty system?

I want to make a prediction for the result of the parliamentary elections. My output will be the % each party receives. There is more than 2 parties so logistic regression is not a viable option. I ...
11
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3answers
2k views

Can regression trees predict continuously?

Suppose I have a smooth function like $f(x, y) = x^2+y^2$. I have a training set $D \subsetneq \{((x, y), f(x,y)) | (x,y) \in \mathbb{R}^2\}$ and, of course, I don't know $f$ although I can evaluate $...
11
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3answers
7k views

Relationship between KS, AUROC, and Gini

Common model validation statistics like the Kolmogorov–Smirnov test (KS), AUROC, and Gini coefficient are all functionally related. However, my question has to do with proving how these are all ...
10
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2answers
2k views

Machine Learning Steps

Which of the below set of steps options is the correct one when creating a predictive model? Option 1: First eliminate the most obviously bad predictors, and preprocess the remaining if needed, then ...
10
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4answers
962 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 ...
10
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2answers
3k views

Machine Learning Best Practices for Big Dataset

I am about to graduate from my Master and had learnt about machine learning as well as performed research projects with it. I wonder about the best practices in the industry when performing machine ...
10
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1answer
17k views

Server log analysis using machine learning

I was assigned this task to analyze the server logs of our application which contains exception logs, database logs event logs etc. I am new to machine learning, we use Spark with elastic search and ...
9
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2answers
10k views

How to use Cohen's Kappa as the evaluation metric in GridSearchCV in Scikit Learn?

I have class imbalance in the ratio 1:15 i.e. very low event rate. So to select tuning parameters of GBM in scikit learn I want to use Kappa instead of F1 score. My understanding is Kappa is a better ...
9
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1answer
7k views

R - Interpreting neural networks plot

I know there are similar question on stats.SE, but I didn't find one that fulfills my request; please, before mark the question as a duplicate, ping me in the comment. I run a neural network based on ...
9
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3answers
618 views

Which, if any, machine learning algorithms are accepted as being a good tradeoff between explainability and prediction?

Machine learning texts describing algorithms such as gradient boosting machines or neural networks often comment that these models are good at prediction, but this comes at the price of a loss of ...
9
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6answers
790 views

What are some of the best practices for sharing data and models with colleagues?

As a data scientist who recently joined a new team, I wanted to ask the community how they share data and models among their colleagues. Currently I have to resort to storing data in some central ...
9
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3answers
6k views

Export weights (formula) from Random Forest Regressor in Scikit-Learn

I trained a prediction model with Scikit Learn in Python (Random Forest Regressor) and I want to extract somehow the weights of each feature to create an excel tool for manual prediction. The only ...
8
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2answers
3k views

Is it valid to shuffle time-series data for a prediction task?

I have a time-series dataset that records some participants' daily features from wearable sensors and their daily mood status. The goal is to use one day's daily features and predict the next day's ...
8
votes
1answer
751 views

Ideas for prospect scoring model

I have to think about a model to identify prospects (companies) that have a high chance of being converted into clients, and I'm looking for advice on what kind of model could be of use. The ...
8
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2answers
83 views

Which classification algorithms are negatively affected by class imbalances?

I've seen a few posts and papers floating around the web (mostly those related to over/undersampling, SMOTE, and cost-sensitive training) that, when discussing class imbalance, specify that certain ...
8
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2answers
102 views

Model for Differing Number of Rows per Observation

Looking to build a response model (click or no click) on marketing data which displays varying number of offers to a person. I don't want to model which offer they click but do they click any of the ...
7
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2answers
20k views

How to interpret a decision tree correctly?

I'm trying to work out if I'm correctly interpreting a decision tree found online. The dependent variable of this decision tree is Credit Rating which has two classes, Bad or Good. The root of this ...
7
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2answers
4k views

How does one deploy a model, after building it in Python or Matlab?

I have been playing around with a lot of different machine learning models (clustering, neural nets, etc...), but I am sort of stuck on understanding what happens after you finish building the model ...
7
votes
2answers
832 views

How would you describe the trade-off between model interpretability and model prediction power in layman's terms?

I know it depends on the data and question asked but imagine a scenario that for a given dataset you could either go for a fairly complex nonlinear model (hard to interpret though) giving you a better ...
7
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3answers
14k views

TypeError: Expected binary or unicode string, got [

ERROR SUMMARY: I'm getting the following error: TypeError: Expected binary or unicode string, got [ BACKGROUND: I have several features that are histories of ...
6
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4answers
8k views

Why aren't languages like C, C++ used for data analytics instead of R, Python?

I have started learning data science using R, however I have C++ as a subject this semester, and my project is to predict the outcome of a game using C++. I have not come across many instances (close ...
6
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3answers
672 views

Data driven approach to define a churn user

I'm trying to define a churn prediction model for an online service (betting/gambling). A lot of papers talk about churn analysis/prediction for telco companies where defining a churn user is ...
6
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5answers
511 views

Can Machine Learning be applied in software developement [closed]

I'm from programming background. I'm now learning Analytics. I'm learning concepts from basic statistics to model building like linear regression, logistic regression, time-series analysis, etc., As ...
6
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2answers
1k views

Improve a regression model and feature selection

I am working on Azure ML Studio and try to create a regression model to predict a numerical value. I will try to describe my features and what I have done until now. My data with about 3 million rows ...
6
votes
2answers
145 views

Naive about which Naive Bayes in article

Working with the Naive Bayes spam filtering article on Wikipedia (https://en.wikipedia.org/wiki/Naive_Bayes_spam_filtering) Is it a binary multinomial equation or a Bernoulli form or some other? In ...
6
votes
3answers
130 views

What is the best algorithm/solution for predicting the following?

I have a dataset that comprises 76 countries, and 6 columns of distinct quantitative variables, which are the mean values of that variable relative to each country: If I were to take a random sample ...
6
votes
1answer
5k views

How to use survival analysis for predictive maintenance for time series data?

So, I have a dataset with daily operating conditions for different machines and a flag saying if it failed or not. Here is a snapshot of the data. How can I use survival analysis or any other ...
6
votes
1answer
64k views

TypeError: float() argument must be a string or a number, not 'function'

I am trying to clean the data. But I don't know how to remove a function from a column in data frame. At row number 473 it show column N has a function . How it should be filtered out ?
6
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2answers
5k views

Why are RNN/LSTM preferred in time series analysis and not other NN?

I had recently a great discussion about the advantages of RNN/LSTM in time series analysis in comparison to other Neural Networks like MLP or CNN. The other side said, that: The NN just have to be ...
6
votes
2answers
707 views

How can I predict the acceptance of an article by publisher?

I am working on this project where I have to predict the acceptance probability of a literary article, let's say a research paper by a publisher, which in this case would be a Journal. I would like ...
6
votes
2answers
7k views

Looking for a strong Phd Topic in Predictive Analytics in the context of Big Data

I'm going to start a Computer Science phd this year and for that I need a research topic. I am interested in Predictive Analytics in the context of Big Data. I am interested by the area of Education (...
6
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3answers
339 views

Regression: How to deal with positive skewness in continuous target variable

I'm working on a regression problem. My aim is to "learn" the distribution of a continuous target $y$ as good as possible to make predictions. My model looks like: $$y_i=\beta X_i + u_i.$$ $y$ is ...
6
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4answers
2k views

Is it possible to cluster data according to a target?

I was wondering if there exists techniques to cluster data according to a target. For example, suppose we want to find groups of customers likely to churn: Target is churn. We want to find clusters ...
6
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2answers
8k views

How to predict customer's next purchase

Suppose we want to predict what customer will buy during his next visit to the Electronic Shop based on his past purchase history. I know that it is a very broad question, but I am new to machine ...
6
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2answers
87 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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