Dataframe

What is Stacking of Models in Machine Learning?

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The last Ensemble method we will discuss in this series is called stacking (short for stacked generalization). It is based on a simple idea: instead of using trivial functions (such as hard voting) to aggregate the predictions of all predictors in an ensemble, why don’t we train a model to perform this aggregation? Figure below … Read more

Introduction to Dimensionality Reduction

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The text discusses the curse of dimensionality in machine learning, highlighting challenges in high-dimensional spaces. It suggests reducing features to improve training efficiency and visualization, while addressing potential information loss and risks of overfitting with increased dimensions. Dimensionality reduction techniques will be explored further.

Sending Data in Unstructured File Form

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Unstructured data files consist of a series of bits. The file doesn’t separate the bits from each other in any way. You can’t simply look into the file and see any structure because there isn’t any to see. Unstructured file formats rely on the file user to know how to interpret the data. For example, … Read more

Random Forests | Machine Learning from Scratch

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As we have discussed, a Random Forest is an ensemble of Decision Trees, generally trained via the bagging method (or sometimes pasting), typically with max_samples set to the size of the training set. Instead of building a BaggingClassifier and passing it a DecisionTreeClassifier, you can instead use the RandomForestClassifier class, which is more convenient and … Read more

Accessing Data in Structured Flat-File Form

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In many cases, the data you need to work with won’t appear within a library, such as the toy datasets in the Scikit-learn library. Real-world data usually appears in a file of some type, and a flat file presents the easiest kind of file to work with. In a flat file, the data appears as … Read more

How can A linear model learn non-linear/discrete patterns?

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Introduction During model development, one of the techniques that many don’t experiment with is feature discretization. The core idea is to transform a continuous feature into discrete features, mostly one-hot encoded. 𝐖𝐡𝐲 𝐰𝐨𝐮𝐥𝐝 𝐰𝐞 𝐝𝐨 𝐭𝐡𝐚𝐭? My rationale for using feature discretization has almost always been simple: “It just makes sense to discretize a feature.” … Read more

Datasets Importing and exporting in Python.

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Python Feature Image

What is Dataset? Datasets are container of data in python. It can work as data storage for the various algorithms in python. and also a primary storage of data in Data Science. Below I will be discussing how to import a datasets as dataframe in python. For this post I’ll be using a public dataset … Read more