Sanjana Shah

How do I sort a dictionary by value?

Absolutely! Sorting a dictionary by its values in Python is a common task, especially when you need to organize data based on importance, frequency, or size. But since dictionaries themselves are unordered collections (prior to Python 3.7), you’ll need to use a little trick with sorted(). Here's a quick and…

Python

Answered Apr 16, 2025 · 1.0K Views Read answer →

Explain how to implement tfidf in python.To implement tf-idf in Python, we need to import necessary libraries. Let us discuss that with the help of a dataset?

Here, smsspamcollection is a dataset contains messages as spam and ham. We need to transform all the words into vectors. Text preprocessing, tokenizing and the ability to filter out stop words are all included in CountVectorizer, which builds a dictionary of features and transforms documents to feature vectors.

Data Science

Answered Dec 24, 2019 · 2.3K Views Read answer →

Explain how normalization of features is better while preprocessing a model?

Normalization refers to rescaling real valued numeric attributes into the range 0 and 1. It is useful to scale the input attributes for a model that depends on the magnitude of values, such as distance measures algorithm used in models like k-nearest neighbors or clustering and in the preparation of coefficients in…

Data Science

Answered Nov 30, 2019 · 1.6K Views Read answer →

Explain ROC curve.

ROC or Receiver Operating Characteristic curve is a graphical representation that gives an idea between True Positive rate against False Positive Rate at various threshold values. It gives an idea to set an optimum threshold value which will decide the probability assign a class. A low threshold value we will put most…

Data Science

Answered Nov 30, 2019 · 2.1K Views Read answer →

A user wants to compute the entropy of 0-1 vector many times. Is there a faster way to do this?

He used the following code def entropy(labels): """ Computes entropy of 0-1 vector. """ n_labels = len(labels) if n_labels

Data Science

Answered Nov 17, 2019 · 1.6K Views Read answer →

Explain with a case study how to visualize the train and test data of a Decision Classification system in Python

First we import the model and the dataset and split for training and testing # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset dataset = pd.read_csv('Social_Network_Ads.csv') X = dataset.iloc[:, [2, 3]].values y = dataset.iloc

Data Science

Answered Nov 9, 2019 · 4.3K Views Read answer →

A user is trying to implement the decision tree regressor algorithm on some training data but when he calls fit() he gets an error.

(trainingData, testData) = data.randomSplit([0.7, 0.3]) vecAssembler = VectorAssembler(inputCols=["_1", "_2", "_3", "_4", "_5", "_6", "_7", "_8", "_9", "_10"], outputCol="features") dt = DecisionTreeRegressor(featuresCol="features", labelCol="_11") dt_model = dt.fit(trainingData)

Data Science

Answered Nov 5, 2019 · 1.5K Views Read answer →

Explain how to implement decision in R

First we import the dataset # Importing the dataset com_sale dataset = read.csv(file.choose()) Now we encode the target feature as factor # Encoding the target feature as factor cut(dataset$TaxableIncome,2) cut(dataset$TaxableIncome,c(0,30000)) dataset$TaxableIncome=cut(dataset$TaxableIncome,2,labels=c("Risky","Good"))

Data Science

Answered Nov 4, 2019 · 1.5K Views Read answer →