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Linear Regression for Diabetes dataset - Lesson 1

Import needed libraries

[1]

Load the diabetes dataset, divided into X data and y features

[2]

(442, 10)
[ 0.03807591  0.05068012  0.06169621  0.02187239 -0.0442235  -0.03482076
 -0.04340085 -0.00259226  0.01990749 -0.01764613]

Select just one feature to target for this exercise

[3]

(442,)

[9]

(442, 1)
[[ 0.06169621]
 [-0.05147406]
 [ 0.04445121]
 [-0.01159501]
 [-0.03638469]
 [-0.04069594]
 [-0.04716281]
 [-0.00189471]
 [ 0.06169621]
 [ 0.03906215]
 [-0.08380842]
 [ 0.01750591]
 [-0.02884001]
 [-0.00189471]
 [-0.02560657]
 [-0.01806189]
 [ 0.04229559]
 [ 0.01211685]
 [-0.0105172 ]
 [-0.01806189]
 [-0.05686312]
 [-0.02237314]
 [-0.00405033]
 [ 0.06061839]
 [ 0.03582872]
 [-0.01267283]
 [-0.07734155]
 [ 0.05954058]
 [-0.02129532]
 [-0.00620595]
 [ 0.04445121]
 [-0.06548562]
 [ 0.12528712]
 [-0.05039625]
 [-0.06332999]
 [-0.03099563]
 [ 0.02289497]
 [ 0.01103904]
 [ 0.07139652]
 [ 0.01427248]
 [-0.00836158]
 [-0.06764124]
 [-0.0105172 ]
 [-0.02345095]
 [ 0.06816308]
 [-0.03530688]
 [-0.01159501]
 [-0.0730303 ]
 [-0.04177375]
 [ 0.01427248]
 [-0.00728377]
 [ 0.0164281 ]
 [-0.00943939]
 [-0.01590626]
 [ 0.0250506 ]
 [-0.04931844]
 [ 0.04121778]
 [-0.06332999]
 [-0.06440781]
 [-0.02560657]
 [-0.00405033]
 [ 0.00457217]
 [-0.00728377]
 [-0.0374625 ]
 [-0.02560657]
 [-0.02452876]
 [-0.01806189]
 [-0.01482845]
 [-0.02991782]
 [-0.046085  ]
 [-0.06979687]
 [ 0.03367309]
 [-0.00405033]
 [-0.02021751]
 [ 0.00241654]
 [-0.03099563]
 [ 0.02828403]
 [-0.03638469]
 [-0.05794093]
 [-0.0374625 ]
 [ 0.01211685]
 [-0.02237314]
 [-0.03530688]
 [ 0.00996123]
 [-0.03961813]
 [ 0.07139652]
 [-0.07518593]
 [-0.00620595]
 [-0.04069594]
 [-0.04824063]
 [-0.02560657]
 [ 0.0519959 ]
 [ 0.00457217]
 [-0.06440781]
 [-0.01698407]
 [-0.05794093]
 [ 0.00996123]
 [ 0.08864151]
 [-0.00512814]
 [-0.06440781]
 [ 0.01750591]
 [-0.04500719]
 [ 0.02828403]
 [ 0.04121778]
 [ 0.06492964]
 [-0.03207344]
 [-0.07626374]
 [ 0.04984027]
 [ 0.04552903]
 [-0.00943939]
 [-0.03207344]
 [ 0.00457217]
 [ 0.02073935]
 [ 0.01427248]
 [ 0.11019775]
 [ 0.00133873]
 [ 0.05846277]
 [-0.02129532]
 [-0.0105172 ]
 [-0.04716281]
 [ 0.00457217]
 [ 0.01750591]
 [ 0.08109682]
 [ 0.0347509 ]
 [ 0.02397278]
 [-0.00836158]
 [-0.06117437]
 [-0.00189471]
 [-0.06225218]
 [ 0.0164281 ]
 [ 0.09618619]
 [-0.06979687]
 [-0.02129532]
 [-0.05362969]
 [ 0.0433734 ]
 [ 0.05630715]
 [-0.0816528 ]
 [ 0.04984027]
 [ 0.11127556]
 [ 0.06169621]
 [ 0.01427248]
 [ 0.04768465]
 [ 0.01211685]
 [ 0.00564998]
 [ 0.04660684]
 [ 0.12852056]
 [ 0.05954058]
 [ 0.09295276]
 [ 0.01535029]
 [-0.00512814]
 [ 0.0703187 ]
 [-0.00405033]
 [-0.00081689]
 [-0.04392938]
 [ 0.02073935]
 [ 0.06061839]
 [-0.0105172 ]
 [-0.03315126]
 [-0.06548562]
 [ 0.0433734 ]
 [-0.06225218]
 [ 0.06385183]
 [ 0.03043966]
 [ 0.07247433]
 [-0.0191397 ]
 [-0.06656343]
 [-0.06009656]
 [ 0.06924089]
 [ 0.05954058]
 [-0.02668438]
 [-0.02021751]
 [-0.046085  ]
 [ 0.07139652]
 [-0.07949718]
 [ 0.00996123]
 [-0.03854032]
 [ 0.01966154]
 [ 0.02720622]
 [-0.00836158]
 [-0.01590626]
 [ 0.00457217]
 [-0.04285156]
 [ 0.00564998]
 [-0.03530688]
 [ 0.02397278]
 [-0.01806189]
 [ 0.04229559]
 [-0.0547075 ]
 [-0.00297252]
 [-0.06656343]
 [-0.01267283]
 [-0.04177375]
 [-0.03099563]
 [-0.00512814]
 [-0.05901875]
 [ 0.0250506 ]
 [-0.046085  ]
 [ 0.00349435]
 [ 0.05415152]
 [-0.04500719]
 [-0.05794093]
 [-0.05578531]
 [ 0.00133873]
 [ 0.03043966]
 [ 0.00672779]
 [ 0.04660684]
 [ 0.02612841]
 [ 0.04552903]
 [ 0.04013997]
 [-0.01806189]
 [ 0.01427248]
 [ 0.03690653]
 [ 0.00349435]
 [-0.07087468]
 [-0.03315126]
 [ 0.09403057]
 [ 0.03582872]
 [ 0.03151747]
 [-0.06548562]
 [-0.04177375]
 [-0.03961813]
 [-0.03854032]
 [-0.02560657]
 [-0.02345095]
 [-0.06656343]
 [ 0.03259528]
 [-0.046085  ]
 [-0.02991782]
 [-0.01267283]
 [-0.01590626]
 [ 0.07139652]
 [-0.03099563]
 [ 0.00026092]
 [ 0.03690653]
 [ 0.03906215]
 [-0.01482845]
 [ 0.00672779]
 [-0.06871905]
 [-0.00943939]
 [ 0.01966154]
 [ 0.07462995]
 [-0.00836158]
 [-0.02345095]
 [-0.046085  ]
 [ 0.05415152]
 [-0.03530688]
 [-0.03207344]
 [-0.0816528 ]
 [ 0.04768465]
 [ 0.06061839]
 [ 0.05630715]
 [ 0.09834182]
 [ 0.05954058]
 [ 0.03367309]
 [ 0.05630715]
 [-0.06548562]
 [ 0.16085492]
 [-0.05578531]
 [-0.02452876]
 [-0.03638469]
 [-0.00836158]
 [-0.04177375]
 [ 0.12744274]
 [-0.07734155]
 [ 0.02828403]
 [-0.02560657]
 [-0.06225218]
 [-0.00081689]
 [ 0.08864151]
 [-0.03207344]
 [ 0.03043966]
 [ 0.00888341]
 [ 0.00672779]
 [-0.02021751]
 [-0.02452876]
 [-0.01159501]
 [ 0.02612841]
 [-0.05901875]
 [-0.03638469]
 [-0.02452876]
 [ 0.01858372]
 [-0.0902753 ]
 [-0.00512814]
 [-0.05255187]
 [-0.02237314]
 [-0.02021751]
 [-0.0547075 ]
 [-0.00620595]
 [-0.01698407]
 [ 0.05522933]
 [ 0.07678558]
 [ 0.01858372]
 [-0.02237314]
 [ 0.09295276]
 [-0.03099563]
 [ 0.03906215]
 [-0.06117437]
 [-0.00836158]
 [-0.0374625 ]
 [-0.01375064]
 [ 0.07355214]
 [-0.02452876]
 [ 0.03367309]
 [ 0.0347509 ]
 [-0.03854032]
 [-0.03961813]
 [-0.00189471]
 [-0.03099563]
 [-0.046085  ]
 [ 0.00133873]
 [ 0.06492964]
 [ 0.04013997]
 [-0.02345095]
 [ 0.05307371]
 [ 0.04013997]
 [-0.02021751]
 [ 0.01427248]
 [-0.03422907]
 [ 0.00672779]
 [ 0.00457217]
 [ 0.03043966]
 [ 0.0519959 ]
 [ 0.06169621]
 [-0.00728377]
 [ 0.00564998]
 [ 0.05415152]
 [-0.00836158]
 [ 0.114509  ]
 [ 0.06708527]
 [-0.05578531]
 [ 0.03043966]
 [-0.02560657]
 [ 0.10480869]
 [-0.00620595]
 [-0.04716281]
 [-0.04824063]
 [ 0.08540807]
 [-0.01267283]
 [-0.03315126]
 [-0.00728377]
 [-0.01375064]
 [ 0.05954058]
 [ 0.02181716]
 [ 0.01858372]
 [-0.01159501]
 [-0.00297252]
 [ 0.01750591]
 [-0.02991782]
 [-0.02021751]
 [-0.05794093]
 [ 0.06061839]
 [-0.04069594]
 [-0.07195249]
 [-0.05578531]
 [ 0.04552903]
 [-0.00943939]
 [-0.03315126]
 [ 0.04984027]
 [-0.08488624]
 [ 0.00564998]
 [ 0.02073935]
 [-0.00728377]
 [ 0.10480869]
 [-0.02452876]
 [-0.00620595]
 [-0.03854032]
 [ 0.13714305]
 [ 0.17055523]
 [ 0.00241654]
 [ 0.03798434]
 [-0.05794093]
 [-0.00943939]
 [-0.02345095]
 [-0.0105172 ]
 [-0.03422907]
 [-0.00297252]
 [ 0.06816308]
 [ 0.00996123]
 [ 0.00241654]
 [-0.03854032]
 [ 0.02612841]
 [-0.08919748]
 [ 0.06061839]
 [-0.02884001]
 [-0.02991782]
 [-0.0191397 ]
 [-0.04069594]
 [ 0.01535029]
 [-0.02452876]
 [ 0.00133873]
 [ 0.06924089]
 [-0.06979687]
 [-0.02991782]
 [-0.046085  ]
 [ 0.01858372]
 [ 0.00133873]
 [-0.03099563]
 [-0.00405033]
 [ 0.01535029]
 [ 0.02289497]
 [ 0.04552903]
 [-0.04500719]
 [-0.03315126]
 [ 0.097264  ]
 [ 0.05415152]
 [ 0.12313149]
 [-0.08057499]
 [ 0.09295276]
 [-0.05039625]
 [-0.01159501]
 [-0.0277622 ]
 [ 0.05846277]
 [ 0.08540807]
 [-0.00081689]
 [ 0.00672779]
 [ 0.00888341]
 [ 0.08001901]
 [ 0.07139652]
 [-0.02452876]
 [-0.0547075 ]
 [-0.03638469]
 [ 0.0164281 ]
 [ 0.07786339]
 [-0.03961813]
 [ 0.01103904]
 [-0.04069594]
 [-0.03422907]
 [ 0.00564998]
 [ 0.08864151]
 [-0.03315126]
 [-0.05686312]
 [-0.03099563]
 [ 0.05522933]
 [-0.06009656]
 [ 0.00133873]
 [-0.02345095]
 [-0.07410811]
 [ 0.01966154]
 [-0.01590626]
 [-0.01590626]
 [ 0.03906215]
 [-0.0730303 ]]

Split the training and test data for both X and y

[5]

Select the model and fit it with the training data

[6]

Use test data to predict a line

[7]

Display the results in a plot

[8]