Logistic Regression in Python | Logistic Regression Example | Machine Learning Algorithms | Edureka

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This Edureka Video on Logistic Regression in Python will give you basic understanding of Logistic Regression Machine Learning Algorithm with examples. In this video, you will also get to see demo on Logistic Regression using Python. Below are the topics covered in this tutorial:
1:10 What is Regression?
3:22 What is Logistic Regression: What & Why?
8:43 Linear Vs Logistic Regression
10:13 Logistic Regression Use Cases
12:14 Logistic Regression Example Demo in Python
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[@edurekaIN]

Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka Python Machine Learning Course curriculum, Visit our Website: bit.ly/2OpzQWw

[@srikanthkuchi7743]

Thank you so much

[@kamakhyasingh9994]

It's an awesome explanation, Thank you very much, Please share the source code & datasets to my mail id : [e-mail]

[@sanatansuryavikram]

Shrey 1 second ago hi what if the labels , dependent variable is 7 and 8 do you have to change it to 0- and 1 or do i keep it as it is to perform logistic regression pleas reply asap.

[@edurekaIN]

Hi Shrey, it has to be dichotomous. So if there are only two categories, you can transform the labels. Hope that solves your query.

[@BriteRoy]

How do you speak so flawlessly without fumbling or pausing even for once. Hats off.

[@ShubhamKumar-fy1fl]

In the world full of greed no one is providing knowledge for free. Edureka you are doing great job 👍

[@himanshushekharsingh5270]

Just to clear my concept on logistic regression i searched L R and saw this video. It is perfectly explained by the instructor. Each and every part is well explained. Glad to see this video. A big thumbs up👍 and Thanks.

[@poornaacharya6910]

You guys are awesome! Explained the concept very clearly and in an understandable way. Thanks a lot!!!

[@maheshkandrekula424]

What is the real practical application of this titanic data set ?

[@sriharitha9985]

I really felt very happy with your explanation, very useful for begginers

[@edurekaIN]

Glad it was helpful! Keep learning with us .

[@astrovert.ed2321]

This one hour video has given immense clarity and confidence. Thanks team!

[@sayanbanerjee362]

"Over here" great job! 👍🏻

[@sandeeppanchal8615]

Hi, presentation is really good. Anybody can understand it easily. Thanks for such wonderful lecture. Input: Our prediction can go to ~ 82% if we can fill the null values in 'Age' column with average values and can be done by 2 methods. 1) Fill the null values with the value which is the average of all age. (df['Age].mean(). Where df variable name for our dataframe) 2) Fill the null values by taking the average values with respect to column 'Pclass'. Example: If average age of passengers travelling in 1st class is taken and fill the null values with respect to 1st class. Same is done for 2nd and 3rd class. Average age with respect to 'Pclass' can be assumed from the boxplot of seaborn with 'Age' as x and 'Pclass' as y. Method 2 is better over method 1. Look at the code to fill the null values in 'Age' with respect to 'Pclass'. (train is the variable name of dataframe) ********************************************************************************* def impute_age(cols): Age = cols[0] Pclass = cols[1] if pd.isnull(Age): if Pclass == 1: return 37 elif Pclass == 2: return 29 else: return 24 else: return Age train['Age'] = train[['Age','Pclass']].apply(impute_age,axis=1) ******************************************************************************* My prediction is as follows: Accuracy: 82.02247191011236 ******************************************************************************* Classification Report precision recall f1-score support 0 0.81 0.93 0.86 163 1 0.85 0.65 0.74 104 micro avg 0.82 0.82 0.82 267 macro avg 0.83 0.79 0.80 267 weighted avg 0.82 0.82 0.81 267 ******************************************************************************* Confusion Matrix: [[151 12] [ 36 68]] ******************************************************************************* Predicted 0 1 Actual 0 151 12 1 36 68

[@elebs_d]

God bless you, Thank you so much for this

[@naynadhone5908]

Thank you mam.. got all the concepts...

[@shivaaryaprakash]

You are very very efficient speaker and have delivered great analysis.. thank you

[@dikshaarora7616]

Amazingly defined 👍 Thankyou

[@PushK-yu5ph]

Great video and a very thorough and clear explanation . Helpful session for the day . Thanks a lot !!!

[@chinnaraobiyyala5505]

GREAT EXPLANATION MAM

[@vikashchoubey4570]

very much useful it is. thank you

[@iqrabashir904]

Please make tutorials on path planing in robotics and practical implementation

[@nehareddy4619]

Simply wow. Excellent explanation by you mam. We need professors like u.

[@edurekaIN]

Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@shubhamsahai2492]

Great session! Thank you :)

[@hamzahilori6579]

My goodness! How did you get this good at teaching. 👏👏👏

[@edurekaIN]

You're welcome 😊 Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@aadika45]

Thanks for your video. It makes life easier.

[@edurekaIN]

Glad it helped!

[@ArunKumar-mi2iq]

After many videos , I got a nice explanation. Kudos to you mam ❤️

[@edurekaIN]

We are super happy that Edureka is helping you learn better. Your support means a lot to us and it motivated us to create even better learning content and courses experience for you . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@shavkatyuldashov235]

It's so understandable lesson! Thank you.

[@khalidhasan1793]

It's a great tutorial. Take a bow..

[@edurekaIN]

Thank you 😊 Glad it helped !!

[@smnazmussadat9424]

Thanks, really helpful

[@bilalbaloch9366]

well explained , My concepts about logistic regression have cleared . Thank you

[@edurekaIN]

Hey Bilal, we are glad you feel this way. Do subscribe and hit the bell icon to never miss an update from us in the future. Cheers!

[@gautamar1455]

wow very rich in content explained well

[@surendra2227]

Great explanation 👌 👍 👏 😀

[@Mithilesh165]

Thanks Edureka....your videos are of high quality ...

[@KamleshSharma-si2rq]

One of the best tutorial ever,Mam can you pls share the dataset and source code...Thank you.

[@edurekaIN]

Hey Kamlesh, we are glad you loved the video. Do mention your email ID over here and we will send the files to you. Cheers!

[@hariprakashroyal569]

Well Explained mam thnx

[@dikshamakkar2850]

Explanation is tooo good.... Thnkz alot😊

[@anuradhabalasubramanian9845]

Fantabulous Presentation Mam!

[@edurekaIN]

Good To know our vedios are helping you learn better :) Stay connected with us and keep learning ! Do subscribe the channel for more updates : )

[@viseshsolution74]

very good explanation

[@akshunair3367]

Loved the way the lesson is taught.

[@rajamoorthy1969]

Outstanding explanation. I am pursuing AI Silver from Pixel Tests but your way of explanation is by far the best one. Thanks for sharing your knowledge. Sharing is caring indeed.

[@edurekaIN]

We are very glad to hear that your a learning well with our contents 😊 continue to learn with us and don't forget to subscribe our channel so that you don't miss any updates !

[@HJ-uy6ez]

You did an excellent job, thank you very much!

[@edurekaIN]

You're welcome 😊 Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@jayanthck1782]

Best explanation on logistic regression thank u so much..

[@shaikyasmin2559]

Thank you mam ,your video very clear ,good help us

[@edurekaIN]

Thanks for the compliment Yasmin, we are glad you loved the video. Do subscribe to the channel and hit the bell icon to never miss an update from us in the future. Cheers!

[@shaikyasmin2559]

@@edurekaIN OK mam

[@amishachourpagar9925]

Thank you mam you explained very well love it😀❤️❤️❤️

[@edurekaIN]

Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@samarthgarg4639]

Just a suggestion, if you also share the data being analysed in the videos, it would be a big help to the ones who are watching

[@edurekaIN]

Hi Samarth, thanks for the feedback. We will definitely look into your suggestion. Please mention your email id (it will not be published). We will forward the data to your email address.

[@80amnesia]

very useful real case example

[@abdellatifthabet568]

thank you ma'am.. keep it up

[@sandeepkumarghosh9531]

Great explanation within a short span of time.This lecture has been very helpful.Thank you mam!

[@flyeagle320]

Wonderful tutorial

[@edurekaIN]

Thank you so much 😊

[@deeptikhanvilkar5983]

Very good explanation for each line of code. Loved it

[@nitinmalhotra423]

Thanks Edureka got all the concepts cleared.

[@rakhipatil2372]

Nice video..Please provide the data set

[@puthayallaiah5586]

Thank you mam for vaulable class on logistics regrations and it gives a clear underatanding to me for alogirthms development in ML

[@banothanilkumar1140]

Thanks you madam it very clear cut explanation

[@vivianogwuihe5201]

The real definition of a Queen. Thank you for this.

[@edurekaIN]

Hi : ) We really are glad to hear this ! Truly feels good that our team is delivering and making your learning easier :) Keep learning with us .Stay connected with our channel and team :) . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@ashutoshgupta8059]

Beautiful

[@sureshkumarbevara8069]

Thank you, This is very helpful for my studies.

[@edurekaIN]

Thanks Suresh!

[@DuyKDao]

Thx u. Very clear instruction

[@sahilgoura691]

The video is very nice. The way our concepts are getting cleared. Please give us the link to download the notebook which you created as titanic.

[@viveksthanam]

Hello Can you also make a video on how to plot these predicted values.

[@edurekaIN]

Hey Vivek, we will definitely look into your suggestions. We update our channel regularly, stay tuned and never miss out on our updates. Cheers :)

[@nayanbire1102]

Thank you so much! Very helpful!

[@edurekaIN]

Good To know our videos are helping you learn better :) Stay connected with us and keep learning ! Do subscribe the channel for more updates : )

[@yash-vh9tk]

Wow. Great explanation

[@siddharthkshirsagar2545]

Best explanation on regression so far thank u so much

[@adityapawar7279]

A very helpful video.Thank you for the brief tutorial on using Jupyter notebook.

[@edurekaIN]

Hi Aditya, thank you for watching our video. Do subscribe, like and share to stay connected with us. Cheers!

[@sirishareddy1390]

how to get dataset?

[@krutarthkhatri5243]

best explanation of logistic regression

[@simransimran6766]

Best explanation ever

[@swarupdas9103]

Great explanation,pls share me the datasets

[@darshanabhole]

helpfull..thnku

[@swarnaharigmailcom]

very clearly explained.Hats off Mam

[@abhisekdey9430]

Thank you so much ma'am. Really its a great tutorial.

[@VIVEKYADAV-gc1ti]

Mam i got 💯% accuracy at Titanic Dataset 💪💪💪💪✊✊👍👍👍

[@krishnaaggarwal9228]

very well explained ,thank you for such good explanation...

[@sriharitha9985]

Hi team, wanted to share a good feedback with you, really missed your university, I was training for ML In some reputed university where I cannot mention the name, however I missed you guys, but following you explanation in KZbin instead of unversity recordings, thank you so much for the help .

[@edurekaIN]

We are super happy that Edureka is helping you learn better. Your support means a lot to us and it motivated us to create even better learning content and courses experience for you . Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@Raos-Academy]

Thank you soo much very nice class

[@sureshkumaratkuri1053]

Excellent explanation. The way you prepare PPTs to explain the concepts is matchless in the industry. keep it up.

[@srivanimrecw6584]

excellent

[@geetikabansal2196]

Thankyou Soooooo Much Ma'am!!!!!!

[@wahabkhan9319]

great video

[@Modern_revolution]

Thanks

[@Yash-cu4gq]

I really like ur explanation mam!! I have got answers for so many doubts with ur explanation. Can u please tell me where to find this excellent notes?? Want more videos on ML😊

[@edurekaIN]

Hi Yashwanth, Thanks for the compliment. We are so glad to hear that you liked our videos. You can always refer to the Machine Learning Playlist of Edureka for more such helpful videos. Here's a link to the playlist kzbin.info/www/bejne/hpuTn5iPitVsisU

[@pallaviaparna5536]

Wonderful explanation madam

[@edurekaIN]

Thank You 😊 Glad it was helpful!! Keep learning with us..

[@shreyastc8975]

Can you please provide data sets as well

[@shreyastc8975]

Wonderful explaination. 👏👏

[@divyadarbe]

Thank you Madam! very good explanation

[@abhayvashokan5580]

Awesome! Really liked it. Live presentations are never this good.

[@matitiudeforever8155]

perfect !! freaking awesome !!...subscribed

[@edurekaIN]

Hey Matitiude, thanks for subscribing! We are glad you loved the video. Do take a look at our other videos too and stay tuned for future updates. Cheers!

[@harishsahu8543]

Wonderful explanation mam. One polite request from my side mam, please could we get the dataset so we can also work on this data set

[@edurekaIN]

We are happy that Edureka is helping you learn better ! We are happy to have learners like you :) Please share your mail id to share the data sheets :) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@doddabasavareddy5833]

Great explain..from where can I fetch dataset?

[@edurekaIN]

We are happy that Edureka is helping you learn better ! We are happy to have learners like you :) Please share your mail id to share the data sheets :) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )

[@LaeTech]

yes

[@rajivgupta6573]

Titanic Survivors Accuracy score can be increased to ~84% Do this, X_train,X_test,y_train,y_test = train_test_split(X,y, test_size = 0.2, random_state = 33) You might get error in some cases, so also change this, model = LogisticRegression(solver='lbfgs',max_iter=10000) Output print(classification_report(y_test,y_pred)) precision recall f1-score support 0 0.84 0.91 0.87 111 1 0.83 0.72 0.77 67 accuracy 0.84 178 macro avg 0.83 0.81 0.82 178 weighted avg 0.84 0.84 0.83 178

[@zahedulislamchowdhury2279]

Thanks for Nice lecture . please send data set list for practices.

[@edurekaIN]

Definitely ! We are glad to have learners like you .Drop your mail id in the comment section for us to share the data sheets or source codes :) Do subscribe our channel and hit that bell icon to never miss an video from our channel .

[@muhammadiqbalbazmi9275]

Thanks a lot, Sister. Keep it up.

[@usmanmalik2182]

Very well explain. Keep it up Edureka! Team

[@rajivgupta6573]

SUV Prediction Instead of removing the gender column, you can include that in the model to increase the accuracy to ~90%. For that just do label encoding for column in data.columns: if data[column].dtype == np.number: continue data[column] = LabelEncoder().fit_transform(data[column]) change this too X_train,X_test,y_train,y_test = train_test_split(X,y, test_size = 0.2, random_state = 30) model = LogisticRegression(solver = 'lbfgs',max_iter = 10000) Output 0.9

[@NamedAfterColor]

Thank you so much.

[@solankitarun911]

Thank u..😇

[@v9054]

Excellent presentation.

[@edurekaIN]

Thank you.

[@louisadibe3189]

Nice video,more way of wrangling the data to view NA : titanic_data.isnull().any()

[@maheshvangala8472]

Thank you so much 😍😍

[@rishird5635]

She is simply wow..Btw can i have the notebook?

[@edurekaIN]

Hey Rishi, glad you loved the video. Please do mention your email id(we won't publish it) so that we can mail the files to you. Cheers!

[@rishird5635]

edureka! Thanks..but I did it meanwhile watching the video..thanks again

[@rahulgurgude]

can you provide dataset along with tutorial ? or link to get it? on kaggle many datasets are there with 'titanic' name

[@edurekaIN]

Hi ! Good to know that our videos are helping you to learn better 😊 Please share your mail id to share the data sheets, We’ll update you soon . Do subscribe the channel for more updates.

[@MayankGoel447]

Thank you for such a wonderful lesson!