https://www.dataschool.io/simple-guide-to-confusion-matrix-terminology/#:~:text=A%20confusion%20matrix%20is%20a,the%20true%20values%20are%20known.&text=The%20classifier%20made%20a%20total,the%20presence%20of%20that%20disease).
https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62
Posted in Data Mining, Data Mining
https://www.statisticshowto.com/spearman-rank-correlation-definition-calculate/
Posted in Uncategorized
https://elentra.healthsci.queensu.ca/assets/modules/types-of-data/symmetrical_and_asymmetrical_data.html
Posted in Uncategorized
https://www.geeksforgeeks.org/absolute-and-relative-frequency-in-r-programming/
Posted in Uncategorized
code for exercise :
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
#a library(arules) data(Groceries) Groceries #b myrules=apriori(Groceries) inspect(myrules) #c myrules=apriori(Groceries,parameter=list(supp=0.05,conf=0.05)) #d inspect(myrules) myrules=apriori(Groceries,parameter=list(minlen=2)) #e myrules=apriori(Groceries,parameter=list(minlen=1)) inspect(myrules) #f myrules=apriori(Groceries,parameter=list(supp=0.01,conf=0.01,minlen=3)) #g inspect(myrules[20]) #answer lift value: Used to judge the strength of the association rule #if lift value is greater than> 1 some usefulness in that rule #the larger the lift is the greater is the strength of the association #https://www.dataminingapps.com/2017/04/what-is-the-lift-value-in-association-rule-mining/ #h cc=sort(myrules,by="lift") inspect(cc[1:10]) #i hh=subset(myrules,subset=lhs %pin% "pork" & lift>1.2) #pin is using as matching function to match character inspect(hh) |
Posted in Data Mining
K={1, 1.1, 5, 5.1, 1.5, 5.2, 7.9, 1.2, 8.1, 9}
Total item=10
iter1:
m1=5 m2=9
K1={1, 1.1, 5, 5.1, 1.5, 5.2, 1.2} K2={7.9, 8.1, 9}
m1=2.87==approx(3) m2=8.333==approx(9)
iter(2):
K1={1, 1.1, 5, 5.1, 1.5, 5.2, 1.2} ; K2={7.9, 8.1, 9}
m1=approx(3) m2=approx(9)
So, here same mean twice. so we have to stop.
Posted in Data Mining, Data Mining
K-means clustering Algorithm for manually finding from observation:
Step 1: Take mean value
Step 2: Find nearest number of mean and put in cluster
Step 3: Repeat one and two until we get same mean
K={2,3,4,10,11,12,20,25,30}
k=2 [it means we have to create 2 clusters]
iter1:
m1=4 m2=12
k1={2,3,4} [according to nearest distance of 4]
so mean m1=3
k2={10,11,12,20,25,30}
m2=108/6=18
iter2:
k1={2,3,4,10}
m1=4.75==approc(5)
k2={11,12,20,25,30}
m2=19.6==approx(20)
Iter 3:
K1={2,3,4,10,11,12} K2={20,25,30}
m1=7 m2=25
k1={2,3,4,10,11,12} k2={20,25,30}
m1=7, m2=25
Same mean twice. Thus we are getting same mean we have to stop.
Posted in Data Mining, Data Mining
https://towardsdatascience.com/who-is-a-data-engineer-how-to-become-a-data-engineer-1167ddc12811
https://medium.com/datadriveninvestor/python-vs-r-choosing-the-best-tool-for-ai-ml-data-science-7e0c2295e243
Posted in Career/Earning, Data Science
ArrayList in Java:
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 |
package com.zakilive; import java.util.ArrayList; public class Main { public static void main(String[] args) { // working with arraylist ArrayList words=new ArrayList<>(); words.add("hello"); //string words.add("there"); words.add(9); //integer words.add(12.00); //double words.add('H'); //character int item1= (int) words.get(2); double item2= (double) words.get(3); String item3= (String) words.get(0); System.out.println(item1+item2); } } |
Generics:
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 |
package com.zakilive; import java.util.ArrayList; import java.util.LinkedList; public class Main { public static void main(String[] args) { // working with arraylist ArrayList<String> words=new ArrayList<String>(); words.add("hello"); //string words.add("there"); words.add("9"); //integer // words.add(12.00); //double // words.add('H'); //character // int item1= (int) words.get(2); // double item2= (double) words.get(3); String item3= (String) words.get(2); System.out.println(item3); // System.out.println(item1+item2); LinkedList<Integer> numbers=new LinkedList<Integer>(); numbers.add(100); numbers.add(200); numbers.removeFirst(); for(int number: numbers) { System.out.println(number); } } } |
LinkedList is faster for manipulation but slower for retrieval and ArrayList is slower for manipulation but faster for retrieval
Posted in Data Structure, Java
Ensemble Models:
Basics
Boosting
Ranmdom Forests
Support Vector Machines
Basics
Linear Classification
Nonlinear Classification
Properties of SVMs
Discriminant Analysis
Basics
Exercise:
We are going to create some data mining models for classification and compare their performance. The goal with our models is still.
Posted in Data Mining, Data Mining
Design of network topology
Determine:
Number of input nodes
Too few nodes => misclassification
Too many nodes=> overfitting
Problems with dollar sign:
https://stackoverflow.com/questions/42560090/what-is-the-meaning-of-the-dollar-sign-in-r-function
Problem with tilde sign:
https://stackoverflow.com/questions/14976331/use-of-tilde-in-r-programming-language?noredirect=1&lq=1
Posted in Data Mining, Data Mining
Software Engineer | Polyglot Programmer | Gym Lover | Cyclist | Algorithm Addict | Programming and Research enthusiast | Life Long Passionate Learner | Love CSE, Backend and Data
Hi, thanks for your interest on my blog 🙂 I am Syed Ahmed Zaki, from Germany. This is my blog “Zakilive.Com” for sharing my knowledge and passion with you all.
I was born in a beautiful country of south asia named Bangladesh. I am a Computer Science and Engineering graduate and currently doing my post graduation in Germany. I am passionate, dedicated, hardworking about my tasks and fond of Algorithms, Competitive Programming, Mathematics, Research in data science(Machine Learning, AI, NLP, Deep Learning), bioinformatics and IoT. I also love software engineering. In software development field I prefer Web Application Engineering.
In my bachelor study life, I tried to participate in several programming contests(online, onsite, intra etc.) and passed some time in ACM training class for sharpening my logical skills. As an ordinary people it was little bit tough for me alongside with academic pressure, thesis and research paper writing but I love challenges so I always tried to push my limits though still I need to improve a lot in everything but I always trust in this quote “Hard work beats talent”. That quote I have learned from my life through bodybuilding of 6 years since 2012 and after losing 33 KG fat in 4 months from 101 KG I developed my fit physique, so I respectfully believe in this sentence and relate this with CSE field. I also love to learn from my failures. I hate excuses while working professionally and I love trying to finish my work with perfection till the last moment before deadline.
I also love to explore and play with new technologies and try to implement it with innovative ideas. In my bachelor university life, I always tried to learn from the basics of Computer Science. So, I have tried to gather Networking to Database Knowledge, OS fundamentals to OOP etc. all fundamental core basics in my skillset in a practical approach.
Alongside with developing some web applications in core php and laravel framework I have also tried to build games with unity3d game engine, built 2 android apps, experimented machine learning with python, data mining with WEKA, AI chatbot, IoT based weather station and some more project works for my undergraduate courses. As I am language and platform agnostic, I enjoyed and learned a lot from all of these works. I also love teamwork. Alongside software engineering and different extra curricular activities I also love teaching. I am also proficient at working with linux and windows based OSes and I feel so lucky if I get chance to contribute in opensource projects. In my linkedin profile you will find more details about me.
However, I am actually a knowledge seeker and life long passionate learner who tries to make his weakness as strength, I was a serious student of all the courses in CS academia that can solve real life problems as I love to explore knowledge in a crafted manner. I love to study books, blogs or whatever philosophically solve my curiosity. For that, I maintain a good collection of various technological, scientific and philosophical books in my small library. Knowledge sharing, analytical thinking, practice and passing the passion of mine with you is one of my motivations for running this blog. I practice to hone my skills with trying to improve my programming and developing skillset day by day and what I learn, I never forget to share here for you.
In my free time I love to do cycling or gym or play racing games in my android phone or watch animated movies and also love to promote positive, fit and healthy lifestyle among people.
Connect with me:
Currently I am working with python technologies. If you have any opportunity/business to work with me or any other query kindly say just hi to me at my mail:
[email protected]