Random Forest ML Algorithm
The random forest algorithm is used in industrial applications such as finding out whether a loan applicant is low-risk or high-risk, predicting the failure of mechanical parts in automobile engines and predicting social media share scores and performance scores. Ensemble a multiple decision tree and voting the right prediction is what random forest do.
There are several applications where a RF analysis can be applied. We will discuss some of the sectors where random forest can be applied. We will also look closer when the random forest analysis comes into the role.
Banking Sector: The banking sector consists of most users. There are many loyal customers and also fraud customers. To determine whether the customer is a loyal or fraud, Random forest analysis comes in. With the help of a random forest algorithm in machine learning, we can easily determine whether the customer is fraud or loyal. A system uses a set of a random algorithm which identifies the fraud transactions by a series of the pattern.
Medicines: Medicines needs a complex combination of specific chemicals. Thus, to identify the great combination in the medicines, Random forest can be used. With the help of machine learning algorithm, it has become easier to detect and predict the drug sensitivity of a medicine. Also, it helps to identify the patient’s disease by analyzing the patient’s medical record.
Stock Market: Machine learning also plays role in the stock market analysis. When you want to know the behavior of the stock market, with the help of Random forest algorithm, the behavior of the stock market can be analyzed. Also, it can show the expected loss or profit which can be produced while purchasing a particular stock.
E-Commerce: When you will find it difficult to recommend or suggest what type of products your customer should see. This is where you can use a random forest algorithm. Using a machine learning system, you can suggest the products which will be more likely for a customer. Using a certain pattern and following the product’s interest of a customer, you can suggest similar products to your customers.