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Text Classification in NLP using Cross Validation and BERT

Mlearning.ai

Some important things that were considered during these selections were: Random Forest : The ultimate feature importance in a Random forest is the average of all decision tree feature importance. A random forest is an ensemble classifier that makes predictions using a variety of decision trees.

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How Can You Check the Accuracy of Your Machine Learning Model?

Pickl AI

So, accuracy is: Case Study: Predicting the Iris Dataset with a Decision Tree The Iris dataset contains flower measurements that classify flowers into three types: Setosa, Versicolor, and Virginica. A Decision Tree model analyses these measurements and makes predictions. The total number of cases is 100.

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Machine Learning Algorithms Explained with Real-World Use Cases

How to Learn Machine Learning

Some examples of supervised algorithms are linear regression, logistic regression, support vector machines, and decision trees. Some of the commonly known algorithms of this category are: Decision Trees : These models split the data into branches to reach a decision, making them highly interpretable.

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Data Science Project?—?Predictive Modeling on Biological Data

Mlearning.ai

You can refer part-I and part-II of this article. import pandas as pd import numpy as np import matplotlib.pyplot as plt df = pd.read_csv('after_eda_data.csv') df.info() Later in this article we will be using the sklearn.pipline.Pipline . This cross-validation results shows without regularization.

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Bias and Variance in Machine Learning

Pickl AI

Here are some examples of variance in machine learning: Overfitting in Decision Trees Decision trees can exhibit high variance if they are allowed to grow too deep, capturing noise and outliers in the training data.

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Understanding and Building Machine Learning Models

Pickl AI

The article also addresses challenges like data quality and model complexity, highlighting the importance of ethical considerations in Machine Learning applications. For example, linear regression is typically used to predict continuous variables, while decision trees are great for classification and regression tasks.

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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. By understanding crucial concepts like Machine Learning, Data Mining, and Predictive Modelling, analysts can communicate effectively, collaborate with cross-functional teams, and make informed decisions that drive business success.