Before going further into neural network algorithm, we need to understand and break down how the algorithm is working. Neural Network Intuition Final Output So h is a non linear function of linear combination of inputs – A multiple logistic regression line Y is a non linear function of linear …

Read More »## 103.3.3 Percentile and Quartile

Now let us discuss percentile and quartile. What a percentile is? Let us see with an example. A student attended an exam along with 999 other students. He secured 68% marks in the exam. So from this, what can we say? Is he clever or not? This is very difficult …

Read More »## 103.3.2 Descriptive Statistics

As soon as we get some data, we can carry out descriptive statistics on it. Basic descriptive statistics gives an idea on the variable and their distribution, we get an overall picture of dataset and it also helps us to create a report on the data. There are 2 types …

Read More »## 103.2.8 Exporting Data

Writing data in CSV file Another important feature available in R is the export function. With this function, the data created in R can be saved into any other format like the csv, xlsx, etc. Just as we used the function read.csv() to read the contents of the CSV file …

Read More »## 103.2.7.a Merge and Join

In the telecom customer complaints data, most of the complaints are generally related to the Services or the Bills. The data on Bill and Complaints will gives us some relation between Bill payers and the Issues they are facing. “./Telecom Data Analysis/Bill.csv” “./Telecom Data Analysis/Complaints.csv” 1. Import the data and …

Read More »## 103.2.7 Merge and Join

In R, we have merge() function to join the data sets into one. Syntax for merge function is: x <- merge(datasets1, dataset2, by="primary_key") The function above merges the dataset1 and dataset2, and saves the merged data into the variable x. We need to mention type of join otherwise the function …

Read More »## 103.2.6 Handling Duplicates

Duplicates can be same or similar based on key (more than one) entries. Like, one customer purchasing multiple times in a single day from the same store. In R, we have a function called duplicated() which can be used to find repeated entries in the dataset.We get the index of …

Read More »## 103.2.5.a Sorting of Data- An Example

In Autodataset we can find out the top or bottom rankers in terms of the specifications of the cars. Like which car has the most mileage, and which car has the least mileage. Sorting helps us in getting such results. The below data set would help us in sorting the …

Read More »## 103.2.5 Sorting of Data

Sorting of the data can be considered as the fundamental part of the Data Analysis. User might want to sort the Names in the Alphabetical order, or wants to sort the Income data in the ascending order to find the highest tax payers, etc. Sorting is helpful in managing the …

Read More »## 103.2.4 Calculated Fields in R

Calculated or the derived field is another important concept in data analysis. Sometimes not only the fields or the rows and columns of the raw data are sufficient for the data analysis, we might also have to do some operations and create some new fields. A new field can be …

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