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It can be used for both classification and regression problems: Decision trees can be used to predict both continuous and discrete values i.e. they work well in both regression and classification tasks.

As decision trees are simple hence they require less effort for understanding an algorithm.

It can capture nonlinear relationships: They can be used to classify non-linearly separable data.

They are very fast and efficient compared to KNN and other classification algorithms.

Easy to understand, interpret, visualize.

The data type of decision tree can handle any type of data whether it is numerical or categorical, or boolean.

Normalization is not required in the Decision Tree.

The decision tree is one of the machine learning algorithms where we don’t worry about its feature scaling. Another one is random forests. Those algorithms are scale-invariant.

It gives us and a good idea about the relative importance of attributes.

Useful in data exploration: A decision tree is one of the fastest way to identify the most significant variables and relations between two or more variables. Decision trees have better power by which we can create new variables/features for the result variable.

Less data preparation needed: In the decision tree, there is no effect by the outsider or missing data in the node of the tree, that’s why the decision tree requires fewer data.

Decision tree is non-parametric: Non-Parametric method is defined as the method in which there are no assumptions about the spatial distribution and the classifier structure.

Concerning the decision tree split for numerical variables millions of records: The time complexity right for operating this operation is very huge keep on increasing as the number of records gets increased decision tree with to numerical variables takes a lot of time for training.

Similarly, this happens in techniques like random forests, XGBoost.

Decision tree for many features: Take more time for training-time complexity to increase as the input increases.

Growing with the tree from the training set: Overfit pruning (pre, post), ensemble method random forest.

Method of overfitting: If we discuss overfitting, it is one of the most difficult methods for decision tree models. The overfitting problem can be solved by setting constraints on the parameters model and pruning method.

Reusability in decision trees: In a decision tree there are small variations in the data that might output in a complex different tree is generated. This is known as variance in the decision tree, which can be decreased by some methods like bagging and boosting.

There is no guarantee to return the 100% efficient decision tree.

Decision Tree Regressor

The decision tree regressor is defined as the decision tree which works for the regression problem, where the ‘y’ is a continuous value. For, in that case, our criteria of choosing is impurity matric. In the classification, the impurity metric was based on Gini Index, Entropy-based, and classification error.

The purpose of using the impurity metric here is that because the probability factor is used in every aspect and that’s why you can calculate any value for the continuous value of ‘y’. So, the criteria of our choosing are MSE – Mean Scale Error. Mean Scale Error is the last decision or the leaf node of the decision tree. If four samples are remaining on which final output will be based, then the average of these four samples will be the value of ‘y’.

Here, N_t is the number of training examples at nodes t, D_tis the training subset at node t, y^((i))is the predicted target value (sample mean):

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What Are The Advantages And Disadvantages Of Machine Learning?

Machine Learning

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Advantages #1 Automation

Machine learning algorithms automate analyzing and interpretation of data and can be used to build predictive models. It eliminates manual data analysis and allows organizations to make data-driven decisions quickly and accurately.

#2 Improved Accuracy

Machine learning algorithms employ pattern recognition techniques to analyze and extract meaningful insights from data, subsequently utilizing these insights to make more accurate predictions. It can be beneficial when dealing with large datasets or constantly changing data.

#3 Cost Reduction

Machine learning algorithms can automate specific processes, reducing labor costs and allowing organizations to focus on more value-adding activities. Additionally, machine learning algorithms often require fewer data and resources to operate, reducing costs.

#4 Scalability

Machine learning algorithms can often be scaled up to handle larger datasets, making them suitable for large-scale applications. It allows organizations to utilize machine learning algorithms to gain insights from their data without needing additional resources.

#5 Increased Efficiency

Machine learning algorithms can automate specific processes, reducing the time required to process and analyze data. It can improve overall efficiency and allow organizations to make more informed decisions.

#1 Data Dependency

Machine learning algorithms are heavily reliant on data for performing any task. These algorithms require large amounts of data to learn and make accurate predictions. With the correct data, the results of a machine-learning model can be balanced and accurate.

#2 Computational Resources

Machine learning algorithms are computationally intensive and require a lot of resources to run. These algorithms can be expensive to train and require a significant upfront investment in hardware and software.

#3 Sampling

Creating a representative sample of the data is essential when using machine learning algorithms. If the sample is as different as expected, the model’s results can be biased accurately.

#4 Privacy and Security

Machine learning algorithms can also help uncover sensitive information from datasets. It means that there are potential privacy and security risks associated with using these algorithms.

#5 Overfitting #6 Time Consumption

Training a machine learning algorithm can be a time-consuming process. Depending on the complexity of the given problem and the amount of data available, training can take anywhere from a few hours to several days.

#7 Black Box Problem

When using machine learning algorithms, it can be challenging to understand how the algorithm reached its decisions and predictions. It can make it difficult to debug and improve the model’s performance.


Improved Accuracy and Efficiency: Machine learning algorithms can process large amounts of data and identify patterns that humans may not be able to detect. It can lead to more accurate predictions and improved efficiency in decision-making.

Automation of Repetitive Tasks: Machine learning systems can automate repetitive and time-consuming tasks, freeing human resources for more complex and creative work.

Data Quality: Machine learning models are only as good as the data they are working upon. The model’s predictions will also be excellent or narrow if the data is of good quality or biased.

Limited Understanding: Machine learning systems can identify patterns and make predictions, but they may not be able to explain how or why they came to a particular decision on a given problem.

High computational cost: Machine learning requires a lot of data and computational power, which can be costly and time-consuming.

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Iphone Se3 Is Coming: Advantages Vs Disadvantages

The iPhone SE3 will arrive to meet the needs of some groups for low-cost small-screen iPhones. The two-year period is approaching, and Apple will make great strides to bring other product lines into the M self-developed chip family, such as the MacBook Air, iMac 27-inch version, etc. In addition, there will be some products that get regular upgrades, such as the iPad Air.

Not to mention the feel of the product, the rounded frame is great in the hand. However, the shortcomings of the product are also very obvious, especially the battery life of the product. During heavy usage, users can only use this device for three or four hours. This means that users will have to charge this smartphone more than 2 times a day. With this device, it is necessary to go out with a power bank.

According to reports, the new generation iPhone SE3 should not change much in terms of appearance. Bloomberg’s Mark Gurman believes that the core changes of the iPhone SE3 should be the A15 and 5G technology. Of course, there will also be improvements to the camera.

iPhone SE3 is a predictable device

The update of this product is not difficult to predict. The A15 processor to be updated is the same as the “iPhone 13” series. Apple will also introduce 5G to align with the current development trend of mobile phones.

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Camera upgrade? Wouldn’t it be to introduce a “movie mode”? There should be nothing more in the camera department. In terms of price, it should remain at $399 – $499, if it is $100 higher, it will collide with the standard version of iPhone 12/13.

If you want to get this device, please pay special attention to the battery!

Although the shortcomings may be very obvious the iPhone SE3 will still have a certain impact on the current smartphone market.

Looking at iPhone SE2 sales, according to Omdia, the 2023 iPhone SE sold 24.2 million units. It is second only to the iPhone 11 with the most sales in 2023 with 64.8 million units.

iPhone SE3 will still be attractive

According to telecomtalk, nearly 40 million iPhone 13 units were sold during Black Friday and Christmas last year. In Apple’s first fiscal quarter of 2023, iPhone 13 sales may exceed 80 million units. Thus, we can clearly see that even if it is a “micro innovation”, the iPhone SE3 will still be attractive.

Sources from the South Korean component industry said that Apple announced to increase its iPhone shipment target by 30% in the first half of 2023, which will bring the total annual iPhone shipments to more than 300 million units for the first time. Analysts also believe that the sales forecast of the iPhone SE3 is about 30 million units.

Look, the iPhone doesn’t have to worry about selling, and the iPhone SE3 doesn’t have to worry about selling!

Cook is about to fulfill his promise!

Let’s go back in time to WWDC 2023 two years ago. At the conference, Apple officially announced that the transition of processors on Macs from Intel to Apple’s own research is expected to take two years.

Which Apple products now have their M internal chips?

In November of the same year, Apple held a special conference and officially launched the MacBook Pro and Air equipped with self-developed M1 chips. The stronger performance and battery life shocked many people.

At the spring conference in April 2023, Apple launched a new and colorful iMac. This design is the first since the iMac came out in 1998. It uses the M1 chip, which is thinner than previous Intel models, a 1080P front-facing camera, and a 24-inch 4.5K display.

At the same conference, Apple also launched the M1 version of the iPad Pro. At the end of last year, Apple held another press conference, launched the 14- and 16-inch MacBook Pro with new designs. The company also upgraded the previous M1 chip, turning it into the more powerful M1 Pro and M1 Max.

What products will use M chips at the spring conference?

The first is the MacBook Air. The iMac 27-inch version may use a new design in the way of the 24-inch version with M-series processors. In addition, the Mac mini will also upgrade from the M1 to the M2 processor. There will also be a better iPad Air 5. If the transition from the iPad Air 3 to the Air 4 is a big change, the Air 5 is a small upgrade at best—mainly the decentralization of some technology from the iPad Pro.


The upcoming spring conference will undoubtedly have a number of PC products with self-developed M-series chips. These will include MacBook Air, iMac, or Mac mini. The regular iteration of the iPhone SE3 will also attract a lot of consumers. However, it has its significant pros and cons.

Types And Measures Of Risk Averse With Advantages

Definition of Risk Averse

Risk averse refers to investors who prefer lower risk over a high rate of returns. They choose to invest their money to earn a guaranteed return, even if it is less, so there remains little or no risk of loss. Generally, the rate of returns remains the same or exceeds slightly depending upon inflation for risk averse investors.

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Risk averse describes the attitude of the investors willing to get a guaranteed return. There is always a risk in investment, but higher returns also attract higher risks. Some investors don’t want to risk their savings getting subsumed with any kind of loss. Hence, they prefer to invest in such investments where they can constantly earn, no matter low or high. The high rate of return does not attract these kinds of investors but gets facilitated by the idea of earning constantly, and due to their lower risk appetite, they want to take a very low risk.


Consider investments like fixed deposits, certificate deposits, or other fixed-income instruments. These kinds of investments offer fixed returns with no or very low risks. An investor who is risk averse would consider such investments for the portfolio to maintain the risk at the lowest level possible.

Types of Investors Risk Averse

There are three types of investors depending upon their way of dealing with the risks:

Risk averse: Such investors avoid risk as much as they can. They prefer a lower rate of return with no risk rather than a high rate with higher risk, as they are afraid to bear any loss in their investments.

Risk Neutral: Such investors neither take too much risk nor avoid risks. They take a calculated risk because they don’t want to bear heavy losses. They usually take medium risks to get a medium or high rate of return.

Risk Loving: Such investors love to take risks, and they look at investment as a gamble in which they can earn a huge rate of return or bear huge losses. They are not afraid of losses because they always get lured by the high rate of returns.

Measures of Risk Averse

Measures of Risk Averse are:

1. Absolute Risk Averse (ARA)

When the risk is high, u(c) curvature will also get higher. However, there is a measure ‘Arrow-Pratt measure of absolute risk aversion that stays constant with respect to these transformations. It is named Arrow Prat measure after the names of the economists Kenneth Arrow and John W. Pratt. It is defined as

A (c) = – un (c)

u1 (c)


2. Relative Risk Aversion (RRA)

The Arrow-Pratt measure of relative risk aversion (RRA) is defined as

R (c) = cA (c) = –cun (c)

u1 (c)


u(c) represents the utility curve as a function of wealth being “c” It is not like ARA, whose units are $-1; the RRA measure is a dimensionless measure due to which it is applied universally. This measure of risk-averse is still valid.

The implication of increasing/decreasing absolute and relative risk aversion: The implication of increasing or decreasing absolute and relative risk aversion helps form the portfolio with one asset risky and the other risk-free. If the investor’s wealth increases, then there is an increase in the risk asset; likewise, if there is a decrease in the investor’s wealth, the investor will choose to increase the risk-free assets.

3. Portfolio Theory

A=dE(c) / dσ

An = dE(c) / d nõn


Investment without fear: A risk averse investor can invest without any fear of getting losses as the money invested here provides a return guarantee. This attracts investors who don’t want to bear any kind of loss in investment.

Constant return: Risk averse investors enjoy the constant return on their investment. They get almost the same or similar returns.

Low risk: There is a very low or almost no risk for risk averse investors.

Loss of opportunity: The main fallback of risk averse approach is that the investor loses the opportunity of earning a high return as they are not ready to take any significant risk.

Almost No Increase in Return: The returns the investors get are almost the same as there is no increment in the return, or a very little increase in return can be seen.

Dependent On Inflation: The increase in the rate of return for risk averse investors is dependent on inflation, which means the rate of return increases only when there is inflation in the country.


Every investor has their own preference for investments. Risk averse investors are those who are not attracted by high returns or a chance of getting a huge profit. They just don’t want their investment to bear any kind of loss; they want guaranteed returns on investments regardless of low returns.

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Advantages Of How Python Argparse() Works

Introduction to Python argparse

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import argparse parser = argparse.ArgumentParser(description='This is default value of desc')

Here we have imported the argparse module using the import statement.

Then an argument parser object is created named “parser”.

The default argument value for the “description” is also set.

Note: As such, the above piece of code will not provide any output over the screen.

How does Parsing in Command-Line works?

Once we have defined all of the arguments, we can pass the sequence of arguments as strings to the below function.

parse_args(): If we do not pass the arguments to this function, then the arguments will be taken up from sys.argv[1:], by default.

GNU/POSIX syntax is utilized to process the options further, so you can also pass the options and arguments in a mixed sequence, and it will not impact the process.

Finally, the parse_args() function will return a value, which indeed is the namespace that consists of arguments to the command.

The object holds the argument value as an attribute. If the argument dest is “myopt”, then you can use the command in the below-mentioned format to access that value myopt.

How does Python argparse() Work?

Given below examples shows the working of python argparse():

Example #1


import argparse parser = argparse.ArgumentParser(description='Understand functioning') parser.add_argument('-x', action="store_true", default=False) parser.add_argument('-y', action="store", dest="y") parser.add_argument('-z', action="store", dest="z", type=int) print (parser.parse_args(['-x', '-yval', '-z', '3']))



To a single character option, there are multiple ways in which the values can be passed.

The value type linked with ‘z’ in the above program’s output is an integer, as we had specifically mentioned to the ArgumentParser to convert the argument before storing it.

Moreover, “Long” option names, having one or more characters in their names, are also handled in a similar fashion in python.

Example #2 – With “Long option names”


import argparse parser = argparse.ArgumentParser(description='How argparse() deals with Long option names') parser.add_argument('-- no argument', action="store_true", default=False) parser.add_argument('-- withargument', action="store", dest="witharg") parser.add_argument('-- withargument2', action="store", dest="witharg2", type=int) print (parser.parse_args([ '-- noargument', '-- withargument', 'val', '-- withargument2=3' ]))



And the results are similar, this validating the notion of “Long” option names, having one or more characters in their names are also handled in a similar fashion in python.

Argument Actions While using argparse() in Python

Whenever an argument is encountered, there are six built-in actions that can be instantaneously triggered.

store: It converts the value into a different type first and then stores the same. By default, this is the action that comes into the picture if any other is not defined.

store_const: Rather than saving the value that is coming up from the argument passed, it saves the value that is defined as a part of the argument specification itself.

store_true / store_false: This action is utilized to take care of the boolean switches when it comes to using the argparse() functionality. Primarily, it is utilized to save the boolean values.

append: If in case the arguments are repeated during the usage of argparse() function, then append action is used to save these multiple values in the form of a list.

append_const: If in case the arguments are repeated in the argument specification during the usage of argparse() function, then append_const action is used to save these multiple values in the form of a list.

version: version action is utilized to print the version details about the program.

Advantages of Python argparse Library

It allows setting the name of the program.

Enables to view the custom usage help.

Moreover, Text help for both before and after the arguments.

The prefix charts can also be customized using the argparse python library.

Moreover, Prefix can also be set for the files that contain the arguments.

It also enables the feature of allowing and disallowing the abbreviations.

Action to be taken 0ver the argument can be pre-set using the python argparse library.

The num of values that are taken up by the option can also be set beforehand itself.


Python argparse() is one of the recommended python modules that take care of multiple scripting needs in an automated fashion by enabling the developer to create reproducible scripts right away from the jupyter notebook code. argparse() enables the user to provide values for the variables during the runtime process.

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6 Different Types Of Iot Products With Advantages

Introduction to IoT Products

In today’s fast-growing world, the trending technology present in the market named the Internet of Things (IoT) is widely used to transmit data from one place to another place using the internet. And for doing this the IoT devices are used. The IoT devices are the products that have the software, wireless sensors and other computer devices installed in it. These products are connected to the internet and used to transmit data without any human intervention. For example, the traffic sensor device installed in a car which can be used to identify traffic ahead and notify the person accordingly.

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Different Types of IoT Products

For reducing the human effort and also make the process automated there are several types of IoT devices present in the market which are used daily. Some of them are mentioned below:

1. Single Board Computer

Source: fossbytes

The single-board computer is a type of IoT product that can be used in computing devices. The single-board computer has various networking options like Bluetooth chip, Ethernet, and Wi-Fi.

2. Amazon Echo

The Amazon Echo is Bluetooth speaker that recognize the voice and can be controlled by voice to play music. The device is supported by wi-fi connectivity and the device uses the cloud platform to perform its functions. When the user gives any instruction the device process the request and gives output. This device can also be integrated with a home automation device to control the devices.

3. Digital Watches

4. Security Systems

The other IoT product is cameras which are IP enabled which sues the local Wi-Fi connection. The footage of the camera can be seen from anywhere in the mobile phones which increases the importance of these types of cameras. The security system can also generate an alarm and can send a message to the owner to inform about any suspicious activity.

5. Sensors

The sensors are the most important product which uses the IoT technology. The sensors are mostly used in factories, buildings, energy, and many other sectors. Any product which uses the IoT uses the sensors for its design. In sensor, there is a transducer that converts the input signal into another form. The sensors are designed to sense surrounding conditions and take appropriate action according to that condition. And after detecting the event the sensors communicate to the connected system so that further action can be taken. The surrounding condition can be any factor like temperature, sound, light, gas or any chemical component.

6. Actuators

Advantages of IoT Products 1. Making of Home Appliances Automatic 2. Support for LOC Monitoring

The IoT products can be applied to LOC for capturing the images and monitoring the activities at LOC. And then the report can be created from that input. The devices can be automatically captured the movement to save life at LOC. The device can trigger the alarm immediately if it notices any suspicious activity and can alert the military. These devices are installed very easily and do not require any maintenance.

3. IoT Products Can Communicate with Each Other

The IoT products are designed such that they are inter-compatible. It can be better understood by example i.e. Google Home. The google home not only used to control home appliances but also to control google’s assistant. The google assistant helps to play music, news, translate anything to some other language. The google assistant also provides every possible information as it is directly connected to the internet. For example, if a person wants to know the current temperature he can ask to google assistant and it will automatically tell the current temperature. The person can get any information by just saying to google assistant.


In the current scenario of market share, the IoT products have captured a major area that is using in every sector. These products can be installed easily and can be used in homes, industries and other organizations. The main aim of these products is to make human work easy and reduce human efforts to do daily routine work.

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