Ames house prices
Ames ia The Ames Housing dataset was compiled by Dean De Cock for use in data science.
With 81 predictors...
2027
31/12
 
  Partecipanti 37 Sottomissioni 1513  
 

The Ames Housing dataset was compiled by Dean De Cock for use in data science.

With 81 predictors describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.

See DeCook “Ames Housing dataset” description in Data Sets.
See Kaggle competition “House Prices: Advanced Regression Techniques”

Submissions are evaluated on Root-Mean-Squared-Error (RMSE) between the logarithm of the predicted value and the logarithm of the observed sales price. (Taking logs means that errors in predicting expensive houses and cheap houses will affect the result equally.)

RMSE = sqrt( mean( ( log(y) – log(haty) )^2 ) )

During the competition, the leaderboard displays your partial score, which is the RMSE for 735 (random) houses of the test set.
At the end of the contest, the leaderboard will display the final score, which is the RMSE for the remaining 735 houses of the test set. The final score will determine the final winner. This method prevents users from overfitting to the leaderboard.

Maximum team size = 3

train <- read.csv(“train.csv”, stringsAsFactors=F)
test <- read.csv(“test.csv”, , stringsAsFactors=F)

fit = lm(log(SalePrice) ~ Yr.Sold + Mo.Sold + Bedroom.AbvGr + Lot.Area, data=train)
yhat = exp( predict(fit, newdata=test) )

write.table(file=“mySubmission.txt”, yhat, row.names = FALSE, col.names = FALSE)

See datadocumentation.txt – full description of the data, prepared by Dean De Cock

The training data has 82 columns which include 23 nominal, 23 ordinal, 14 discrete, and 20 continuous variables (and 2 additional observation identifiers). Here’s a brief version of what you’ll find in the data description file.

SalePrice – the property’s sale price in dollars. This is the target variable that you’re trying to predict.

Order: Observation number
PID: Parcel identification number
MS.SubClass: The building class
MS.Zoning: The general zoning classification
Lot.Frontage: Linear feet of street connected to property
Lot.Area: Lot size in square feet
Street: Type of road access
Alley: Type of alley access
Lot.Shape: General shape of property
Land.Contour: Flatness of the property
Utilities: Type of utilities available
Lot.Config: Lot configuration
Land.Slope: Slope of property
Neighborhood: Physical locations within Ames city limits
Condition.1: Proximity to main road or railroad
Condition.2: Proximity to main road or railroad (if a second is present)
Bldg.Type: Type of dwelling
House.Style: Style of dwelling
Overall.Qual: Overall material and finish quality
Overall.Cond: Overall condition rating
Year.Built: Original construction date
Year.Remod.Add: Remodel date
Roof.Style: Type of roof
Roof.Matl: Roof material
Exterior.1st: Exterior covering on house
Exterior.2nd: Exterior covering on house (if more than one material)
Mas.Vnr.Type: Masonry veneer type
Mas.Vnr.Area: Masonry veneer area in square feet
Exter.Qual: Exterior material quality
Exter.Cond: Present condition of the material on the exterior
Foundation: Type of foundation
Bsmt.Qual: Height of the basement
Bsmt.Cond: General condition of the basement
Bsmt.Exposure: Walkout or garden level basement walls
Bsmt.Fin.Type.1: Quality of basement finished area
Bsmt.Fin.SF.1: Type 1 finished square feet
Bsmt.Fin.Type.2: Quality of second finished area (if present)
Bsmt.Fin.SF.2: Type 2 finished square feet
Bsmt.Unf.SF: Unfinished square feet of basement area
Total.Bsmt.SF: Total square feet of basement area
Heating: Type of heating
Heating.QC: Heating quality and condition
Central.Air: Central air conditioning
Electrical: Electrical system
1st.Flr.SF: First Floor square feet
2nd.Flr.SF: Second floor square feet
Low.Qual.Fin.SF: Low quality finished square feet (all floors)
Gr.Liv.Area: Above grade (ground) living area square feet
Bsmt.Full.Bath: Basement full bathrooms
Bsmt.Half.Bath: Basement half bathrooms
Full.Bath: Full bathrooms above grade
Half.Bath: Half baths above grade
Bedroom.AbvGr: Number of bedrooms above basement level
Kitchen.AbvGr: Number of kitchens
Kitchen.Qual: Kitchen quality
Tot.Rms.AbvGrd: Total rooms above grade (does not include bathrooms)
Functional: Home functionality rating
Fireplaces: Number of fireplaces
Fireplace.Qu: Fireplace quality
Garage.Type: Garage location
Garage.Yr.Blt: Year garage was built
Garage.Finish: Interior finish of the garage
Garage.Cars: Size of garage in car capacity
Garage.Area: Size of garage in square feet
Garage.Qual: Garage quality
Garage.Cond: Garage condition
Paved.Drive: Paved driveway
Wood.Deck.SF: Wood deck area in square feet
Open.Porch.SF: Open porch area in square feet
Enclosed.Porch: Enclosed porch area in square feet
3Ssn.Porch: Three season porch area in square feet
Screen.Porch: Screen porch area in square feet
Pool.Area: Pool area in square feet
Pool.QC: Pool quality
Fence: Fence quality
Misc.Feature: Miscellaneous feature not covered in other categories
Misc.Val: $Value of miscellaneous feature
Mo.Sold: Month Sold
Yr.Sold: Year Sold
Sale.Type: Type of sale
Sale.Condition: Condition of sale




Training set train.csv
600 KB
Test set test.csv
600 KB
data documentation datadocumentation.txt
20 KB
Ames Housing dataset decock.pdf
400 KB
Per partecipare bisogna prima autenticarsi
# Nome Punteggio Prove Ultima prova
1 h.akyirefi PARZIALE 38.72% 8 13.11.2016
17:25
2 f.vitti1 PARZIALE 14.53% 36 15.11.2016
17:57
3 r.monetti1 PARZIALE 14.53% 28 15.11.2016
15:42
4 a.guevara PARZIALE 14.52% 16 14.11.2016
20:34
5 g.andromede PARZIALE 14.03% 35 15.11.2016
13:30
6 l.sella PARZIALE 14.03% 35 15.11.2016
13:17
7 a.brambilla73 PARZIALE 14.03% 9 15.11.2016
12:23
8 m.fumagalli68 PARZIALE 13.98% 53 14.11.2016
15:58
9 m.monaldi PARZIALE 13.98% 35 15.11.2016
10:41
10 chiara.gorla PARZIALE 13.84% 61 15.11.2016
09:42
11 f.pirola13 PARZIALE 13.84% 5 15.11.2016
11:44
12 a.galli33 PARZIALE 13.84% 2 15.11.2016
15:30
13 m.fogliata PARZIALE 12.86% 7 15.11.2016
13:30
14 s.dalessio PARZIALE 12.59% 70 15.11.2016
12:52
15 d.caldara1 PARZIALE 12.59% 7 15.11.2016
16:42
16 AVON VALENTINO PARZIALE 12.55% 2 05.11.2016
18:05
17 D.Pagani PARZIALE 12.52% 175 15.11.2016
16:38
18 f.giorgini PARZIALE 12.52% 45 15.11.2016
16:42
19 A.Pizzocri PARZIALE 12.52% 6 15.11.2016
16:43
20 riccardo.parviero PARZIALE 12.35% 43 15.11.2016
15:52
21 d.marzagora PARZIALE 12.35% 23 15.11.2016
15:58
22 elisa.lucci PARZIALE 12.35% 22 15.11.2016
16:01
23 gramaticamarco PARZIALE 12.26% 156 15.11.2016
16:25
24 r.lavelli1 PARZIALE 12.26% 121 15.11.2016
16:10
25 d.gualtieri5 PARZIALE 12.26% 56 15.11.2016
16:12
26 v.angius1 PARZIALE 12.02% 215 14.11.2016
08:36
27 n.vanderhart PARZIALE 12.02% 40 14.11.2016
08:42
28 gpolp PARZIALE 12.02% 50 14.11.2016
20:33
29 f.facciuto PARZIALE 12.02% 28 14.11.2016
23:19
30 e.fabrizi1 PARZIALE 12.02% 25 15.11.2016
08:13
31 m.rosa18 PARZIALE 11.83% 74 14.11.2016
16:03
32 solari.aldo PARZIALE 00 20 11.07.2017
15:55