Using any dataset apply Apriori Algorithm and Anomalies detection methods to the dataset. Source code needed.
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Using any dataset apply Apriori
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- On a time series dataset, what cross-validation approach would you use?For ecoli dataset correctly set train and test data. You should randomly divide the dataset into a training dataset, validation set and an independent test dataset where the training dataset will contain 80% of the samples, the validation set contains 10% of samples, and the test dataset will contain 10% samples, respectively.Write a R-code to find mean, median and mode for your own raw data of 15 observations. Give the suitable labels to the findings.
- Python code How to apply 5 fold cross validation in datasetDATA SOURCE( NEED NEAT HANDWRITTEN SOLUTION ONLY OTHERWISE DOWNVOTE).Use R language to complete assignment. Load the Iris dataset and answer the following questions with the help of R code given. State the descriptive statistics, including maximum, minimum, average, median, range, sum and standard deviation for of Sepal length, sepal width, petal length and petal width. Create and show histogram plots of Sepal length, sepal width, petal length and petal width. In the Question 2, Which histogram plots do resemble normal distribution? Discuss. Create and show a scatter plot of sepal width and sepal length. What trend do you see? Discuss. What other data visualization or analysis can be done on this dataset? Give some ideas. library(psych) library(ggplot2) Data(iris) head(iris) psych::describe(iris) # Create a scatter plot ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Petal.Length, size = Petal.Width, shape = Species)) + geom_point() + scale_color_gradient(low = "blue", high = "red") + labs(title = "Iris Dataset:…