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# How to Build Regression Models in Weka

In this video, we will be showing you how to build regression models in Weka using linear regression and various machine learning algorithms (random forest, support vector machine and neural network). Weka is a GUI-based machine learning that provides access to a complete collection of functionalities to perform data science tasks (no coding) in a point-and-click fashion. This tutorial is suitable for beginners and those wanting to break into data science.

✅ Weka 3 website: https://www.cs.waikato.ac.nz/ml/weka/
✅ Buy the Official Weka 3 Book: https://amzn.to/34MY6LC

#machine-learning #weka

## Buddha Community  1598352300

## Regression: Linear Regression

Machine learning algorithms are not your regular algorithms that we may be used to because they are often described by a combination of some complex statistics and mathematics. Since it is very important to understand the background of any algorithm you want to implement, this could pose a challenge to people with a non-mathematical background as the maths can sap your motivation by slowing you down. In this article, we would be discussing linear and logistic regression and some regression techniques assuming we all have heard or even learnt about the Linear model in Mathematics class at high school. Hopefully, at the end of the article, the concept would be clearer.

**Regression Analysis **is a statistical process for estimating the relationships between the dependent variables (say Y) and one or more independent variables or predictors (X). It explains the changes in the dependent variables with respect to changes in select predictors. Some major uses for regression analysis are in determining the strength of predictors, forecasting an effect, and trend forecasting. It finds the significant relationship between variables and the impact of predictors on dependent variables. In regression, we fit a curve/line (regression/best fit line) to the data points, such that the differences between the distances of data points from the curve/line are minimized.

#regression #machine-learning #beginner #logistic-regression #linear-regression #deep learning 1592023980

## 5 Regression algorithms: Explanation & Implementation in Python

Take your current understanding and skills on machine learning algorithms to the next level with this article. What is regression analysis in simple words? How is it applied in practice for real-world problems? And what is the possible snippet of codes in Python you can use for implementation regression algorithms for various objectives? Let’s forget about boring learning stuff and talk about science and the way it works.

#linear-regression-python #linear-regression #multivariate-regression #regression #python-programming 1601431200

## Polynomial Regression — The “curves” of a linear model

The most glamorous part of a data analytics project/report is, as many would agree, the one where the Machine Learning algorithms do their magic using the data. However, one of the most overlooked part of the process is the preprocessing of data.

A lot more significant effort is put into preparing the data to fit a model on rather than tuning the model to fit the data better. One such preprocessing technique that we intend to disentangle is Polynomial Regression.

#data-science #machine-learning #polynomial-regression #regression #linear-regression 1624653660

## The Best Way to Build a Chatbot in 2021

A useful tool several businesses implement for answering questions that potential customers may have is a chatbot. Many programming languages give web designers several ways on how to make a chatbot for their websites. They are capable of answering basic questions for visitors and offer innovation for businesses.

With the help of programming languages, it is possible to create a chatbot from the ground up to satisfy someone’s needs.

### Plan Out the Chatbot’s Purpose

Before building a chatbot, it is ideal for web designers to determine how it will function on a website. Several chatbot duties center around fulfilling customers’ needs and questions or compiling and optimizing data via transactions.

Some benefits of implementing chatbots include:

• Generating leads for marketing products and services
• Improve work capacity when employees cannot answer questions or during non-business hours
• Reducing errors while providing accurate information to customers or visitors
• Meeting customer demands through instant communication

Some programmers may choose to design a chatbox to function through predefined answers based on the questions customers may input or function by adapting and learning via human input.

#chatbots #latest news #the best way to build a chatbot in 2021 #build #build a chatbot #best way to build a chatbot 1571046022

## Build Your Own Cryptocurrency Blockchain in Python

Cryptocurrency is a decentralized digital currency that uses encryption techniques to regulate the generation of currency units and to verify the transfer of funds. Anonymity, decentralization, and security are among its main features. Cryptocurrency is not regulated or tracked by any centralized authority, government, or bank.

Blockchain, a decentralized peer-to-peer (P2P) network, which is comprised of data blocks, is an integral part of cryptocurrency. These blocks chronologically store information about transactions and adhere to a protocol for inter-node communication and validating new blocks. The data recorded in blocks cannot be altered without the alteration of all subsequent blocks.

In this article, we are going to explain how you can create a simple blockchain using the Python programming language.

Here is the basic blueprint of the Python class we’ll use for creating the blockchain:

``````class Block(object):
def __init__():
pass
#initial structure of the block class
def compute_hash():
pass
#producing the cryptographic hash of each block
class BlockChain(object):
def __init__(self):
#building the chain
def build_genesis(self):
pass
#creating the initial block
def build_block(self, proof_number, previous_hash):
pass
#builds new block and adds to the chain
@staticmethod
def confirm_validity(block, previous_block):
pass
#checks whether the blockchain is valid
pass
# declares data of transactions
@staticmethod
def proof_of_work(last_proof):
pass
#adds to the security of the blockchain
@property
def latest_block(self):
pass
#returns the last block in the chain
``````

Now, let’s explain how the blockchain class works.

## Initial Structure of the Block Class

Here is the code for our initial block class:

``````import hashlib
import time
class Block(object):
def __init__(self, index, proof_number, previous_hash, data, timestamp=None):
self.index = index
self.proof_number = proof_number
self.previous_hash = previous_hash
self.data = data
self.timestamp = timestamp or time.time()
@property
def compute_hash(self):
string_block = "{}{}{}{}{}".format(self.index, self.proof_number, self.previous_hash, self.data, self.timestamp)
return hashlib.sha256(string_block.encode()).hexdigest()
``````

As you can see above, the class constructor or initiation method ( init()) above takes the following parameters:

`self` — just like any other Python class, this parameter is used to refer to the class itself. Any variable associated with the class can be accessed using it.

`index` — it’s used to track the position of a block within the blockchain.

`previous_hash` — it used to reference the hash of the previous block within the blockchain.

`data—it` gives details of the transactions done, for example, the amount bought.

`timestamp—it` inserts a timestamp for all the transactions performed.

The second method in the class, compute_hash , is used to produce the cryptographic hash of each block based on the above values.

As you can see, we imported the SHA-256 algorithm into the cryptocurrency blockchain project to help in getting the hashes of the blocks.

Once the values have been placed inside the hashing module, the algorithm will return a 256-bit string denoting the contents of the block.

So, this is what gives the blockchain immutability. Since each block will be represented by a hash, which will be computed from the hash of the previous block, corrupting any block in the chain will make the other blocks have invalid hashes, resulting in breakage of the whole blockchain network.

## Building the Chain

The whole concept of a blockchain is based on the fact that the blocks are “chained” to each other. Now, we’ll create a blockchain class that will play the critical role of managing the entire chain.

It will keep the transactions data and include other helper methods for completing various roles, such as adding new blocks.

Let’s talk about the helper methods.

Here is the code:

``````class BlockChain(object):
def __init__(self):
self.chain = []
self.current_data = []
self.nodes = set()
self.build_genesis()
``````

The init() constructor method is what instantiates the blockchain.

Here are the roles of its attributes:

self.chain — this variable stores all the blocks.

self.current_data — this variable stores information about the transactions in the block.

self.build_genesis() — this method is used to create the initial block in the chain.

## Building the Genesis Block

The `build_genesis()` method is used for creating the initial block in the chain, that is, a block without any predecessors. The genesis block is what represents the beginning of the blockchain.

To create it, we’ll call the `build_block()` method and give it some default values. The parameters `proof_number` and `previous_hash` are both given a value of zero, though you can give them any value you desire.

Here is the code:

``````def build_genesis(self):
self.build_block(proof_number=0, previous_hash=0)
def build_block(self, proof_number, previous_hash):
block = Block(
index=len(self.chain),
proof_number=proof_number,
previous_hash=previous_hash,
data=self.current_data
)
self.current_data = []
self.chain.append(block)
return block

``````

## Confirming Validity of the Blockchain

The `confirm_validity` method is critical in examining the integrity of the blockchain and making sure inconsistencies are lacking.

As explained earlier, hashes are pivotal for realizing the security of the cryptocurrency blockchain, because any slight alteration in an object will result in the creation of an entirely different hash.

Thus, the `confirm_validity` method utilizes a series of if statements to assess whether the hash of each block has been compromised.

Furthermore, it also compares the hash values of every two successive blocks to identify any anomalies. If the chain is working properly, it returns true; otherwise, it returns false.

Here is the code:

``````def confirm_validity(block, previous_block):
if previous_block.index + 1 != block.index:
return False
elif previous_block.compute_hash != block.previous_hash:
return False
elif block.timestamp <= previous_block.timestamp:
return False
return True

``````

## Declaring Data of Transactions

The `get_data` method is important in declaring the data of transactions on a block. This method takes three parameters (sender’s information, receiver’s information, and amount) and adds the transaction data to the self.current_data list.

Here is the code:

``````def get_data(self, sender, receiver, amount):
self.current_data.append({
'sender': sender,
'amount': amount
})
return True
``````

## Effecting the Proof of Work

In blockchain technology, Proof of Work (PoW) refers to the complexity involved in mining or generating new blocks on the blockchain.

For example, the PoW can be implemented by identifying a number that solves a problem whenever a user completes some computing work. Anyone on the blockchain network should find the number complex to identify but easy to verify — this is the main concept of PoW.

This way, it discourages spamming and compromising the integrity of the network.

In this article, we’ll illustrate how to include a Proof of Work algorithm in a blockchain cryptocurrency project.

## Finalizing With the Last Block

Finally, the latest_block() helper method is used for retrieving the last block on the network, which is actually the current block.

Here is the code:

``````def latest_block(self):
return self.chain[-1]
``````

## Implementing Blockchain Mining

Now, this is the most exciting section!

Initially, the transactions are kept in a list of unverified transactions. Mining refers to the process of placing the unverified transactions in a block and solving the PoW problem. It can be referred to as the computing work involved in verifying the transactions.

If everything has been figured out correctly, a block is created or mined and joined together with the others in the blockchain. If users have successfully mined a block, they are often rewarded for using their computing resources to solve the PoW problem.

Here is the mining method in this simple cryptocurrency blockchain project:

``````def block_mining(self, details_miner):
self.get_data(
sender="0", #it implies that this node has created a new block
quantity=1, #creating a new block (or identifying the proof number) is awarded with 1
)
last_block = self.latest_block
last_proof_number = last_block.proof_number
proof_number = self.proof_of_work(last_proof_number)
last_hash = last_block.compute_hash
block = self.build_block(proof_number, last_hash)
return vars(block)
``````

## Summary

Here is the whole code for our crypto blockchain class in Python:

``````import hashlib
import time
class Block(object):
def __init__(self, index, proof_number, previous_hash, data, timestamp=None):
self.index = index
self.proof_number = proof_number
self.previous_hash = previous_hash
self.data = data
self.timestamp = timestamp or time.time()
@property
def compute_hash(self):
string_block = "{}{}{}{}{}".format(self.index, self.proof_number, self.previous_hash, self.data, self.timestamp)
return hashlib.sha256(string_block.encode()).hexdigest()
def __repr__(self):
return "{} - {} - {} - {} - {}".format(self.index, self.proof_number, self.previous_hash, self.data, self.timestamp)
class BlockChain(object):
def __init__(self):
self.chain = []
self.current_data = []
self.nodes = set()
self.build_genesis()
def build_genesis(self):
self.build_block(proof_number=0, previous_hash=0)
def build_block(self, proof_number, previous_hash):
block = Block(
index=len(self.chain),
proof_number=proof_number,
previous_hash=previous_hash,
data=self.current_data
)
self.current_data = []
self.chain.append(block)
return block
@staticmethod
def confirm_validity(block, previous_block):
if previous_block.index + 1 != block.index:
return False
elif previous_block.compute_hash != block.previous_hash:
return False
elif block.timestamp <= previous_block.timestamp:
return False
return True
self.current_data.append({
'sender': sender,
'amount': amount
})
return True
@staticmethod
def proof_of_work(last_proof):
pass
@property
def latest_block(self):
return self.chain[-1]
def chain_validity(self):
pass
def block_mining(self, details_miner):
self.get_data(
sender="0", #it implies that this node has created a new block
quantity=1, #creating a new block (or identifying the proof number) is awared with 1
)
last_block = self.latest_block
last_proof_number = last_block.proof_number
proof_number = self.proof_of_work(last_proof_number)
last_hash = last_block.compute_hash
block = self.build_block(proof_number, last_hash)
return vars(block)
return True
@staticmethod
def get_block_object(block_data):
return Block(
block_data['index'],
block_data['proof_number'],
block_data['previous_hash'],
block_data['data'],
timestamp=block_data['timestamp']
)
blockchain = BlockChain()
print(blockchain.chain)
last_block = blockchain.latest_block
last_proof_number = last_block.proof_number
proof_number = blockchain.proof_of_work(last_proof_number)
blockchain.get_data(
sender="0", #this means that this node has constructed another block
amount=1, #building a new block (or figuring out the proof number) is awarded with 1
)
last_hash = last_block.compute_hash
block = blockchain.build_block(proof_number, last_hash)
print("WOW, MINING HAS BEEN SUCCESSFUL!")
print(blockchain.chain)
``````

Now, let’s try to run our code to see if we can generate some digital coins…

Wow, it worked!

## Conclusion

That is it!

We hope that this article has assisted you to understand the underlying technology that powers cryptocurrencies such as Bitcoin and Ethereum.

We just illustrated the basic ideas for making your feet wet in the innovative blockchain technology. The project above can still be enhanced by incorporating other features to make it more useful and robust.