Data Science Stack Exchange
Data Science Stack Exchange

Questions tagged [methods]

21 questions
21
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What do "compile", "fit", and "predict" do in Keras sequential models?

I am a little confused between these two parts of Keras sequential models functions. May someone explains what is exactly the job of each one? I mean compile doing forward pass and calculating cost function then pass it through fit to do backward…
user3486308
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How can I learn and apply the scientific method in machine learning?

Rigor Theory. I wish to learn the scientific method and how to apply it in machine learning. Specifically, how to verify that a model captured the pattern in data; how to rigorously reach conclusions based on well-justified empirical…
Mostafa Touny
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4
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2 answers

Perform classification on market basket analysis

I have the following problem that I don't know how to solve: I have the data for different market baskets with a corresponding class. So for example I know: Student - {beer, milk, water} Professional - {nuts, pizza, bananas} Student - {oranges,…
tristndev
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2 answers

Good classifiers when having many labels

I am asking myself, if there is another good method than deep artificial neural networks when trying to classify data with many (>100) labels. Are there any suggestions? For example, logistic regression does not seem to fit, as - in its basic form,…
Xafer
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1 answer

drop columns and rows in one line in pandas

I want to drop a range of rows and columns of a dataframe, I did it as follow: df.drop(df.columns[3:], axis=1, inplace=True) df.drop(df.index[3:], axis=0, inplace=True) Can I do the two processes in one method instead of two? Or is there any more…
Mohamed Abduljawad
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4 answers

Data Science Methodologies

What are the best known Data Science Methodologies today? By methodology I mean a step-by-step phased process that can be used for framing guidance, although I will be grateful for something close too. To help clarify, there are methodologies in the…
Mike Wise
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Can you provide examples of business application of vector autoregressive model?

Vector Autoregressive models are exploited at Economics faculties all around the world. They are just another statistical model that solves problem of forecasting, although in a deeply complexity-uncovering manner. Yet to my surprise, there is no…
user2530062
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What are some method for pre-processing data in OCR?

I have a dataset for a supervised learning task. Each row is a vector with a value of pixmap value in a range [0,255] of gray colormap, each vector is labeled with a character. I have to assign each vector with a character. My Question: What are…
GlossMash
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What is behind "A. Grothendieck scheme theory" in Mondobrain?

Mondobrain proposes a "big data" technology with: a new generation of algorithms based on A. Grothendieck scheme theory (Field Medal) that extract knowledge and rules from data without any model or distance, and that can explore every part of …
Laurent Duval
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Predicting High-School test scores after a disciplinary action

I'm somewhat new to machine learning and have learned to apply many of the basic regression and classification methods using python and various packages. However, approaching this problem has me stumped. To illustrate the problem, I created a…
DataG
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Time-series decomposition to a base level and an effect of another feature

I've got a time-series data (let's denote it as y) and some feature (let's denote it as x). y is dependent on x, but x is often equal to 0. Even then, y is not 0, so we can assume that there's a base level in y which is independent of x.…
jakes
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How do you define the steps to explore the data?

I'm falling in love with data science and I'm spending a lot of time studying it. It seems that a common data science workflow is: Frame the problem Collect the data Clean the data Work on the data Report the results I'm struggling to connect the…
Daniel
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Modeling count data with time-dependent rate

For processes of discrete events occurring in continuous time with time-independent rate, we can use count models like Poisson or Negative Binomial. For discrete events that can occur once per sample in continuous time, with a time-dependent rate,…
Bridgeburners
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How is DS used in the case of Payment Gateways?

I know it's a general question but what type of analytics can be done in this case? How can we apply machine learning models here?
m2rik
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Can distribution values of a target variable be used as features in cross-validation?

I came across an SVM predictive model where the author used the probabilistic distribution value of the target variable as a feature in the feature set. For example: The author built a model for each gesture of each player to guess which gesture…
Climbs_lika_Spyder
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